On August 16th, 2018, a Mw 5.1 earthquake struck the Molise region , inducing 84 earthquake-triggered landslides that predominantly involved soil covers of clayey materials and flysch on gently dipping slopes. To quantify the spatiotemporal landslide activity in the months immediately after the earthquake, a differential SAR interferometry (DInSAR) analysis was performed for a time span from 2 years before to one year after the earthquake, recognising both first-time and reactivated landslides. The results showed a clear increase in landslide activity following the low-magnitude earthquake with respect to the activities recorded in the same months of the previous years. Several coherent landslides (earth slides and earth flows) were observed following seasonally recurrent rainfall events. Such increases were observed for both reactivated and first-time landslides, showing decreases in inactive periods and activity over longer periods. Furthermore, the spatial density distribution of the landslides was investigated in the postseismic time interval along transects perpendicular and parallel to the direction of the tectonic element responsible for the seismic event. An asymmetrical distribution was deduced parallel to the fault strike with a higher number of landslides located inside the compressional sector according to a strike-slip faulting mechanism. Under particular conditions, postseismic ground effects are documented to be as effective as coseismic effects2, inducing or promoting prolonged erosion and perturbations of stream network muss budgets by increasing the sediment load in rivers5. These conditions pertain to natural slopes in tectonically active areas, where seismic shaking can weaken rock masses or soils, leaving them free to be flushed and eroded from hillslopes3.Earthquake-triggered landslides (EqTLs) represent one of the major geological hazards in mountainous and hilly areas and are one of the main seismically induced ground effects6, debris flows or reactivation of pre-existing or coseismic landslides9.Most of the induced ground effects that contribute to these enhanced rates are represented by disrupted and coherent landslides that involve damaged rock masses or loosened soils and regolith7, which can be quantified by a reduction in critical rainfall threshold12 or a reduction in strength that reflects an increase in landslide rates. This erosive response is proved to be linked to the character of seismic shaking3  or the Arias intensity) and is markedly effective in the epicentral areas, where most EqTLs are registered14 and where the most effective tectonic and seismological control in the near-fault region is expected17. The increased disequilibrium after earthquakes results in a fast transient pulse and is recovered over years depending on the earthquake moment magnitude7.Impulsive shaking plays a prominent role in increasing the landscape sensitivity of the involved areas to meteoclimatic forcing after earthquakes18.While increases in erosion and landslide rates were registered after strong earthquakes in recent decades  on predisposed slopes featuring a weak soil cover or weakened substratum and high susceptibility to landslides, this effect could be equally relevant after relatively low-magnitude earthquakes, contributing as an acquired legacy to the aggravation of postseismic rainfall-induced landslide susceptibility19, has also been evaluated postseismic stages, analysing the spatial density and directional distributions with respect to the strike-slip faulting mechanism.Control by tectonic and faulting mechanisms in the distribution of EqTLs in coseismic stages, reported in datasets of ground failures worldwide22 with integration of in situ and thematic data. The multitemporal approach involves large time spans through the stacking of tens to hundreds of SAR images. Additionally, the conventional single-pair DInSAR technique has been employed to monitor landslide displacements25.Satellite SAR interferometry has been largely used for updating landslide inventories, assessing the state of activity by means of multitemporal techniques such as advanced differential synthetic aperture radar interferometry (DInSAR)23, which allows measurement of deformation that occurs in a few days , and (2) impulsive phenomena such as landslide reactivations and nonlinear movements such as the acceleration of a landslide after a rainy period.For this type of study, DInSAR analysis allows the detection of (1) fast movements derived from a single interferogram analysis26.The results of a 3 year-long interferometric analysis aimed at inventorying landslide reactivations after an earthquake are presented here. The case study is represented by the epicentral areas of the August 16th, 2018, Mw 5.1 Montecilfone earthquake, where 84 EqTLs were surveyed, highlighting the relevance of rainfall in aggravating the coseismic scenario. Due to the low earthquake magnitude and the EqTLs detected in the case study, the resulting scenario seems to be overestimated, suggesting a combined action of preparatory and triggering factors2 and is located on the NE side of the Molise region in a portion between the Frentani Mts. and Adriatic coast, representing the external part of the Apennine chain.The study area struck by the Mw 5.1 Montecilfone earthquake is approximately 1000 km29. This geological setting was derived from the early Miocene to Pleistocene uplift of the chain, which led to the current regional morphostructural setting28.This region is characterised by a NE-verging fold-and-thrust belt revealed by the stacking of the most external tectonic units of the southern sector of the chain, locally covered by thrust-top deposits and a late Miocene-Pliocene terrigenous succession30, which involved both surficial and deeper tectonic units derived from the deformation of the buried Apulian domain: (1) a compressive phase (lower Miocene—upper Pliocene), characterised by the development of E-vergent surficial thrusts; (2) a transcurrent phase (upper Pliocene—lower Pleistocene), characterised by the presence of N–S and E–W faulting; and (3) an extensional phase (middle Pleistocene—Holocene), characterised by direct SW–NE and NW–SE fault systems that are still active in the study area, as suggested by seismicity and landslide activity.More specifically, the sector of the Apennines under investigation is the result of three important tectonic phases28; the deposits are mainly composed of scaly clays followed by arenaceous-marly and calcareous-marly flysches27, evaporites and chaotic terrains28 while thick siliciclastic sequences (Plio-Pleistocene) crop out in the foredeep. Since the middle Pleistocene, the study area has been affected by moderate tectonic uplift32 resulting in the formation of regressive sequences and terraced marine deposits that crop out in the hilly relief of Guglionesi, Petacciato and San Giacomo degli Schiavoni villages33. The successions of both domains  are covered by continental, marine and transitional deposits (Quaternary) that crop out widely in alluvial areas and close to the Adriatic coast, where their thickness reaches tens of metres35.The study area presents a thick marine sequence of chain domains (Cenozoic) belonging to the Lagonegrese-Molisan Basin27  landslides and (2) terraced alluvial deposits of both continental and marine environments found near the river network and close to the Adriatic coast, respectively;Foredeep domain: composed of (1) blue clays that pass upwards to sands and conglomerates and ii) marine conglomerate-sandy deposits (Plio-Pleistocene);Chain domain: composed of (1) pelitic flysch belonging to the Vallone Ferrato Fm (Messinian—Tortonian), mainly composed of marls and clayey marls interlayered with sandstones and siltstones; (2) arenaceous flysch belonging to the Faeto Fm ; and (3) scaly clays (lower Miocene—Upper Cretaceous) that form a tectonic melange consisting of clays and marly clays, with typical colouring from green to reddish, with a chaotic structure and micritic intercalations;Top-thrust basin transitional domain: composed of (1) calcarenites belonging to the Palombaro, Casalanguida and Larino Fms (middle Pliocene—lower Pliocene), (2) marly clays (middle Pliocene—lower Pliocene).The lithotechnical units that crop out in the study area can be described as follows27 Fig. :QuaternaThe lithologies that crop out justify a hilly relief with elevations up to 650 m a.s.l. and river valleys of variable extent. The central sector of the study area belongs to the lower basin of the Biferno River, while northern and southern sectors bound the basins of the Trigno and Fortore rivers.36. In fact, it is typified by the presence of more than 28,000 landslides of different sizes and types of movement that cover an area of approximately 4461 km240. In the epicentral area of the 2018 earthquake, approximately 7100 landslides were recognised over time, with sizes ranging from 100 m2 to 3 km2. Regarding the state of activity, dormant landslides account for approximately 72%, while active or stabilised landslides represent approximately 24% and 4%, respectively. These landslides show low to very low velocities and can be classified as flows, slides or complex landslides, according to Hungr et al.41. Moreover, very slow viscous deformation of the soil cover, such as soil creep and solifluction, can affect gently dipping slopes. Landslides are often driven by the presence of tectonic alignments or by fluvial networks and by surface erosion of runoff waters. Gravity-induced deformation mainly involves Quaternary deposits and the shallow and weathered portions of the bedrock. Deep phenomena involve the thick sequences of Plio-Pleistocene clays, especially in coastal areas44.The geotechnical features of the outcropping units make the Molise region one of the most landslide-prone areas in central and southern Italy45 (Mw < 2.0).The study area was struck by a Mw 5.1 earthquake that occurred on August 16th, 2018, at 18:19:04 (UTC) with an epicentre in Montecilfone  ; this event represented the mainshock of a longer seismic sequence, which started on April 25, 2018, and ended on September 4, 2018, and was followed by almost 840 low-magnitude earthquakeshttp://shakemap.rm.ingv.it). Macroseismic surveying was conducted by the INGV QUEST Group46. In general, despite a low-damage scenario with respect to buildings in Montecilfone, Acquaviva Collecroce and Castelmauro municipalities , a higher intensity level (up to VII) can be attributed if earthquake-induced ground effects are considered in accordance with the Environmental Seismic Intensity (ESI) scale47. The distribution of the epicentres appears to be slightly elongated in the E–W direction, similar to the epicentres of the 2002 San Giuliano di Puglia seismic sequence, located approximately 20 km south of the Montecilfone epicentral area. The focal mechanism of the 2018 mainshock indicates a dextral strike-slip rupture45, which is consistent with that elaborated for the 2002 earthquake and is identified in the Individual Seismogenic Source code as ITIS052 (San Giuliano di Puglia) and in the Composite Seismogenic Source code as ITCS003 (Ripabottoni-San Severo) by the Database of Individual Seismogenic Sources v. 3.2.1 (DISS v. 3.2.1- http://diss.rm.ingv.it/diss/). Valensise et al.48 added more information for the 2002 San Giuliano di Puglia earthquake, considering it due to a composite rupture of a 20 km-long segment of an important E–W-trending pre-existing subvertical fault. This event was located on the westward prolongation of the Mattinata fault zone, approximately 15 km west of the presumed western end of the Mw 6.7 rupture of July 30th, 1627 , 30 km east of the Apennines axis. Valensise et al.48 also suggest that the entire system is active but that it is segmented up into 10- to 25 km-long portions. Given the relatively low magnitude of the event, the seismogenic source is not included in the DISS catalogue. Notwithstanding, the 2002 and 2018 Molise seismic sequences highlight the occurrence of active faulting in this area, where relevant earthquakes have not previously been recorded. This zone is located approximately 50 km east of the extensional Appenninic belt and approximately 50 km west of the dextral strike-slip Mattinata fault49.The 2018 Montecilfone mainshock resulted in a low PGA of up to 0.12 g . To eliminate the action of rain alone as the main triggering factor of the surveyed landslides, a statistical analysis of maximum daily and hourly rainfall intensity data was performed by Martino et al.ades see .The EqTLs resulted from the coupled action of simultaneous preparatory and triggering factors characterised by different hazards. The longer-term factor is referred to as the seismic trigger, which has a return period ranging from 150 to 200 years. The shorter-term factor can be attributed to rainfall triggers, characterised by maximum return periods of 17 and 13 years if time windows of 1 h and 3 days are considered, respectively. It follows that the contribution of the earthquake, although prepared by rainfall, appears to be a necessary condition to justify the landslide scenario surveyed immediately after the August 2018 mainshock, implying a coseismic scenario.26, inventorying 84 earthquake-triggered landslides (EqTLs)50 and 4 coseismic ground cracks.In the days immediately after the 2018 Montecilfone earthquake, a detailed field survey of earthquake-induced ground effects was performed by the Sapienza fast-response team51; this procedure focused on the distinction of clear clues for landslide activation (or reactivation). In this way, all surveyed landslides were compared with the available landslide catalogue  to assess the number of landslide reactivations with respect to first occurrences52 in the coseismic interval; this analysis revealed that 37.5% of EqTLs were reactivated pre-existing landslides. The prevalent landslide mechanisms included earth slides and earth flows, which involved slopes with inclinations ranging from 10° to 15° according to lithological unit outcrops in the study area. In particular, the landslides primarily affected surficial soil cover on gentle slopes made up of clays and marly clays (60%) and secondarily flysch (27%) and alluvial or debris deposits (13%).The observed effects were surveyed and geolocalised in the field following the standardised procedure reported in Martino et al.53 (CEDIT), which did not document evidence of past earthquake-induced ground effects in the study area. Only a few landslides and ground cracks are referred to the historical 1805 (Sant’Anna), 1627 (Gargano), 1894 (Lesina), and 1980 (Irpinia) earthquakes that took place in the surrounding area.The surveyed effects were inventoried according to the criteria established for the Italian Catalogue of Earthquake-Induced Ground Failure database54. The frequency distribution of the landslides available in the catalogue shows peaked unimodal right-skewed (positive kurtosis and skewness) distributions for both elevation and slope, with mode values equal to 200–250 m a.s.l. and 20°.The analysis of frequency distributions of total landslides and of slope morphologies in the entire study area with respect to topographic metrics  or lithology provides a summary of the susceptibility of an area to landslidesEqTLs show a unimodal distribution with peaks centred at lower values of 150–200 m a.s.l. and a gradient of 15°. This finding marks the importance of seismic input in controlling landslide occurrence  since landslides occur even at slighter slopes and lower elevations .26, the surveyed EqTLs also show a slight NE-SW directivity in their spatial distribution in accordance with the main morphostructural alignments, such as the fluvial and drainage networks, which represent features of the morphostructural setting.Based on the first analysis reported in Martino et al.26. However, to date, the distribution of EqTLs does not provide evidence supporting the link between the directivity and the strike-slip fault mechanism. Moreover, regarding the distribution with respect to the epicentral distance, a typical decreasing frequency of EqTLs is observed with increasing distance, with an almost symmetrical distribution, especially parallel to the strike of the reliable fault plane  and triggering factors . The unexpected distance of occurrence with respect to the Keefer affected area, which is based on the registered magnitude of the event, allows delineation of the perturbed area, where possible evidence of increased postseismic activity can be assumed.Maximum distances of 7 km for disrupted landslides  and of 18 km for coherent landslides  were surveyed. Based on these epicentral distances, given the magnitude of the earthquake, all the disrupted landslides occurred below the maximum expected distance provided by Keefer26. These destabilising factors acted on mainly clayey  and flysch lithologies, characterised by very low friction angles57 (lower than 22°) resulting in gentle slopes, affected a priori by abundant landslides. The latter show reactivations every year involving shallow soils and eluvium-colluvium covers  resulted in an increased impact on the territory, as testified by the surveyed scenarioIn the following section, evidence or proxies of increased activity have been recorded and are discussed within the framework of the seismotectonic, geo-lithological and morphostructural setting of the area.To evaluate landslide activity in the study area after the Mw 5.1 Montecilfone earthquake , a multitemporal analysis of satellite SAR images over three years across the seismic event was conducted. Evidence of variations in the landslide rate in the postseismic year was investigated and compared with that for “unperturbed” conditions during the two years before the earthquake.52) were accounted for based on the comparison with the available landslide catalogues.In more detail, pivoting the analysis on the date of Montecilfone earthquake , two years before the earthquake  and one year after the earthquake (September 2018–August 2019) were scanned in detail by means of DInSAR. In total, 350 interferograms covering a time span between October 2nd, 2016, and August 1st, 2019, were exploited to detect both the reactivation of pre-existing landslides  and first-time inventoried landslides in the two years before and in the year after the Montecilfone mainshock. Interferometric fringes related to reactivation of pre-existing landslides or first-time landslides ; given this result, continuous activity was assumed if there were no interruptions lasting through at least three consecutive interferograms. In fact, as revealed by the DInSAR analysis, these landslides showed a significant increase in the number of days of movement in the postseismic year with respect to the number of days of movement detected in the two analysed preseismic years. This increase was on average equal to + 57 days (as a positive change between the number of days of movement detected in the postseismic year and the number of days of movement detected in one of the preseismic years) of continuous activity compared to the 2017–2018 preseismic year and equal to + 17 days of movement compared to the 2016–2017 year, reaching increases of + 120, + 140, and + 150 as the changes (Δ) in the number of days of movement for some landslides. The most common mechanism in continuous-type landslides is earthflows (17 landslides), which mainly involves the scaly clays and Faeto flysch formations, and 6 landslides have a complex type of movement. These categories of landslides often originate in clays with an earth slide mechanism where a flow involves landslide deposits at the slope foot. This is the case for the landslides that show the greatest increase (Δ) in the number of days of movement in the postseismic stage compared to the preseismic stages (+ 150 days). Sliding and fast-flow landslide mechanisms are less common among continuous-type landslides .26 as well as with the PGA scenario. In particular, the landslide reactivation density derived over all fishnet cells reported the maximum (red and orange cells) and medium (yellow cells) concentrations in accordance with the shape of the shakemap obtained for the mainshock of August 2018 and with the expected distances of EqTL occurrence59. As reported above, an anomalous increase in the landslide reactivation number was observed during the autumn and winter seasons in the postseismic year. Since the pluviometric regime of autumn and winter after the 2018 earthquake is comparable to those recorded in the same seasons of the years preceding the 2018 earthquake, as described in the following Methods section, we note that the increase in the number of reactivations of landslides is independent on the rainfall but closely linked to the destabilising action that the earthquake caused in the soils outcrops, which reduced the resistance in the medium-long term and would have acted as a preparatory factor for the rainfall-induced reactivations experienced in the postseismic interval.To better assess the destabilising role of the earthquake in increasing landslide activity in the postseismic year in the epicentral area, a landslide density spatial analysis Fig.  was carr54 was also evaluated in the postseismic stage, with the aim of highlighting potentially irreversible modifications in the stability of slopes and landslide activity ascribable to fault mechanisms or directivity of ground motion.Based on the focal mechanism solution of the 2018 Molise earthquake returned by the National Geophysical and Volcanology Institute (INGV) and given the tectonic settings of the area, the N80°W-oriented dextral transcurrent solution may be assumed to be the seismogenic element source of the Mw 5.1 earthquake . The relationship between the orientation of fault slip that generated the earthquake and the landslide occurrence discussed for EqTLs by other Authors6. More specifically, to evaluate the landslide distribution over time, the total number of reactivations of each landslide was considered.To observe the relative distribution of the landslides as a function of the distance from the tectonic elements parallel and perpendicular to the fault strike, two mutually perpendicular transects were reconstructed. These transects were computed for both the preseismic years and the postseismic year. The transects were constructed by projecting all the landslides surveyed across the considered tectonic lineament within a buffer 1.5 km wide on both sides of the two traces, covering the whole epicentral area for a distance greater than that of the Keefer curves for disrupted landslidesFigure Conversely, the distribution of landslide reactivations in the postseismic year projected onto a transect parallel to the fault alignment reveals an asymmetrical distribution. In fact, in the W sector, where compression occurred, the number of landslide reactivations is up to three times greater than that of landslides reactivated in the E sector. The linear distribution of the number of reactivations also indicates a sharp asymmetric and decreasing trend moving away from the epicentre Fig. . An evenNo relevant changes in topographic elevations and gradients are retrieved along the analysed transects. The distribution in the number of reactivations is observed over an alignment characterised by a homogeneous gentle topography with variable heights ranging between 200 and 400 m a.s.l. and low gradients ranging between 10° and 20°. As revealed by the swath profile, a nonnegligible change in morphological metrics (elevation and slope roughness) can be observed on the right bank of the Biferno River towards the NE sector of the area, where a flat valley filled by alluvial deposits is present; thus, this sector should not be considered for a more consistent spatial analysis.26.The results of the DInSAR analysis over a three-year time interval encompassing the seismic event of 2018 highlight the landslide style and distribution of the reactivations before and after the earthquake and during the almost simultaneous pluviometric event, considered a common rainfall patternIn general, autumn and winter, i.e., the wettest seasons, are characterised by the greatest number of reactivations of landslides or by their first occurrence since rainfall acts as a trigger following the saturation of the shallow parts of the lithotypes that crop out. The DInSAR analysis and the available databases of landslides allow us to estimate the number of reactivations of already existing landslides and the number of first-occurrence landslides  in the study area. The most represented types of movement are slow earth landslides, such as flows and planar or rotational slides, mainly involving scaly or marly clays and the Faeto flysch.60. The spatial distribution of the landslide reactivations in the postseismic year marks the epicentral area and reflects the maximum PGA (g) values (0.06–0.075 g up to 0.12 g). This confirms that the seismic shaking experienced by soil could affect the stability of the slope and the equilibrium of pre-existing landslides.Within this susceptible geological and morphological setting, the low-magnitude earthquake and the relatively weak motion . The observed effect appears negligible in the postseismic spring, i.e., more than six months after the earthquake, since the number of reactivations is comparable to that observed in the two years before the earthquake, suggesting how even small earthquakes can lead to rapid changes in slope erosion rates in the clayey hillslopes considered here.In the case of high-magnitude events, this increase in activity is expected to be recovered in the following yearsThe potential contribution of anomalous rainfall as a trigger in landslide activity in the months immediately following the earthquake can be excluded because the area had a similar pluviometric regime over the three years considered. More specifically, in autumn and winter of the postseismic year, i.e., in the rainy season, the total rainfall amounts are lower than those of the 2 years preceding the earthquake, with 463 mm and 542 mm accumulating in six months. Therefore, the rains after the 2018 earthquake cannot be considered the main cause of the exceptional increase in landslides in the postseismic period. Conversely, the earthquake is retained as an aggravation factor that contributed to the rainfall-induced scenario observed in the first postseismic year, playing a leading preparatory role in the slope disequilibrium.To better frame the landslide style of activity before and after the Montecilfone seismic event, a systematic analysis of the state of activity of the reactivated landslides from 09/2016 and 09/2019 was carried out by DInSAR analysis. The total days of activity and the inactivity period were computed as the difference between the first and the last subsequent interferograms where a landslide shows evidence of movement  and the time between two different reactivations . To be consistent, all the time differences were computed based on the date of the master SAR images; thus, a systematic error in landslide timing equal to the revisit time  was introduced.Group I: Seasonally recurrent landslides, with two or more reactivations in the same year (time of inactivity fewer than 150 days);Group II: Yearly reactivated landslides, single reactivation within a year, every 200–450 days;Group III: Continuous landslides with a long time of activity (movement detected for at least 45 days up to 200 days);Group IV: Landslides that were reactivated in only the postseismic year and were inactive for at least two years (time of inactivity greater than 500 days), i.e., which were reactivated at least before autumn 2016 and characterised by a single reactivation over one year.The state of activity of the monitored landslides, expressed in terms of days in which movement is detected in consecutive interferograms and days of inactivity , is shown in Fig. st preseismic year (2017–2018) reveals an increase in the number of reactivated landslides belonging to group IV, which showed no evidence of movement in the two preceding years. Moreover, an increase in the rate of activity of continuous landslides is expressed by an increase in the days of activity during the postseismic year with respect to the previous years. These reactivated landslides reveal an annual or multiannual recurrence and belong to group III. The greatest increase occurred in the postseismic year for the landslides belonging to group I, as they increased in the total number of landslide reactivations. Based on the comparison between the state of activity observed in the postseismic year and that detected in the preseismic years, we can state how the earthquake changed the style and activity of landslide processes, increasing them in absolute number , in the number of reactivations and in the duration of the activity.A comparison among the results obtained for the 1st preseismic year Fig. a regardiAn increase in the rate of landslide occurrence can be deduced by calculating the differentials of the two parameters that describe the state of activity (days of activity and inactivity period) of each landslide between the postseismic year and the preseismic years Fig. c; this iRegarding the deposits involved in the postseismic landslide activations , the landslide movement rates increased in the postseismic year, especially in the three months following the mainshock. Given the registered trend of reactivations, the enhanced rates of landslides recorded after the earthquake might have been driven not only by rainfall or aftershocks but also by the lowered strength of slope soil materials  due to coseismic mainshock shaking, which occurred despite the low magnitude of the 2018 Montecilfone earthquake . The recovery of stability within a few months following the earthquake could be related to the low magnitude of the mainshock; literature data reveal a possible inference of the earthquake magnitude on the occurrence rate over a decade, as the time span for stability recovery varies from 1 year up to 10 years for earthquakes with Mw greater than 6.61. For eluvium and regolith, mechanical damage and ground crack opening could affect the postseismic landslide rate, while for bedrock, joints or bedding planes can form or widen during shaking but influence medium- to long-term slope stability after the earthquake. The postseismic landslides presented here mainly involve outcrops of the shallow soil covers  that would have experienced gravitational disequilibrium, thus justifying, together with the low magnitude of the seismic event, an increased landslide rate in only the first months after the mainshock.Earthquake-induced failures can involve eluvium, regolith and bedrock with different mechanisms68. In general, different types of seismogenic faults can induce several EqTL patterns69. Coseismic landslides triggered by strike-slip faults show a more symmetric distribution across the fault and are distributed in a narrow area71, unlike reverse or normal fault mechanisms, whose spatial density distribution is more concentrated on the hanging wall74. This last feature was also observed for the Italian territory following the 1980 Mw 6.9 Irpinia earthquake, in which an asymmetric distribution of EqTLs characterised by a higher concentration of slope failure on the hanging wall of the seismogenic normal fault was surveyed55. In the case study presented here, both EqTLs  and postseismic landslides show asymmetric distributions, considering the frequency distribution along a transect parallel to the fault strike, with a number of landslide reactivations greater in the W sector and with a maximum near the fault rupture  but also the style and rates of landslide activity in the postseismic years, depending on the earthquake magnitude and a priori landslide susceptibility of the study area. Although the role of the earthquake fault mechanism in the distribution of postseismic landslide activity is far from fully understood, seismic shaking would have contributed to the deferred instability and acted as a preparatory factor on the involved slopes.An asymmetric distribution  of postseismic landslides was also observed in the compressional and tensional zones of the fault rupture. Considering the transect perpendicular to the fault (transect oriented N10°E), an almost symmetric distribution of reactivated landslides can be identified, with a slight prevalence in the compressional zone Fig. . In the The methodology applied here highlights the suitability of satellite DInSAR for detecting impulsive phenomena such as landslide reactivations and nonlinear movements such as the acceleration of a landslide, representing a more suitable approach than advanced multitemporal techniques (A-DInSAR). Remote surveying has proven to be a very effective tool for both evaluating landslide scenarios after a mainshock and discriminating causative or predisposing factors that control the landslide distributions in a long-term window, i.e., several years after the seismic event.Quantifying variations in the state of landslide activity after earthquake occurs is a challenging topic that requires the coupling of field-collected and remotely sensed data. Based on the time period of landslide activity as well as on the duration of inactivity intervals, the nonnegligible effects of earthquake coseismic shaking and postseismic short-to-middle displacement time on landslide processes are highlighted. If force-driven effects due to dynamic actions can be hypothesised and conventionally quantified through pseudostatic or pseudodynamic approaches, the same is not possible for creep-driven phenomena such as earthflows. In these cases, the inference of soil moisture and seasonal saturation of the involved debris covers requires a high number of episodes to perform a reliable statistical analysis of earthquake-induced effects. In this regard, the selected case study offers a rich database to be analysed in terms of both the spatial distribution and time recurrence of landslide events.The remote survey presented here highlights the intensification of landslide activity after a low-magnitude earthquake, which struck slopes featuring very high susceptibility. This transient increase involved the first year after the earthquake. The outcomes obtained here indicate the relevance of combining preparatory and triggering factors in landslide scenarios, which can be relevant in both coseismic and postseismic stages, as retrieved by the analysis of landslide reactivation in the postseismic period.Based on such an analysis, the inference of tectonic and faulting mechanism evident in the coseismic interval, usually surveyed by EqTL distribution, is also evaluated for the postseismic stage, where an asymmetric distribution and a relevant concentration of landslides are registered in compressive sectors parallel to a strike-slip faulting mechanism.This study demonstrates that low-magnitude earthquakes can also play a morphogenetic role in the framework of landscape evolution over short to moderate time periods and proposes a quantitative analysis to output landslide activity variations at a basin scale after an earthquake. Moreover, the approach proposed here, which integrates direct field observations with remotely sensed observations, is promising in terms of reliability and coverage of spatial information.2 based on the differential synthetic aperture radar interferometry (D-InSAR) technique using SARPROZ software.In total, 332 C-band Sentinel-1 SAR images were acquired for a time interval between October 2nd, 2016, and August 1st, 2019, consisting of 167 images in ascending orbital geometry and 165 images in descending orbital geometry, with a revisit time of 6 or 18 days and spatial resolution of 5 × 20 m, in interferometric wide-swath mode Table . More th75). To achieve reliable displacement results, the topographic component was detected and subtracted from differential interferograms. The 30 m-resolution digital elevation model (DEM) from the Shuttle Radar Topography Mission (SRTM) was used to remove the topographic component from the generated interferograms. The possible atmospheric disturbance on the single interferograms was not filtered, as this type of signal  does not affect the pattern of localised landslide fringes.DInSAR is a radar-based technique that exploits the information contained in the phase of at least two SAR images acquired over the same area at different times to obtain interferometric differential maps .The availability of both ascending and descending images allowed us to exploit redundant and independent datasets. The first step of the applied procedure was to fully screen each interferogram to detect spatial phase variations located on the slopes of the whole study area. Once a spatial phase variation was detected, i.e., interferometric fringes were observed, possible evidence of slope deformation could be preliminarily mapped and compared with subsequent interferograms and landslide inventories in the literature.https://idrogeo.isprambiente.it/app/).To drive the investigation of first-time landslides or reactivations of pre-existing landslides, the Italian Landslide catalogue was adopted as a first directory database. In object-oriented research, a single polygon mapped in the official catalogue was considered for counting the number of reactivations. More than 500 reactivations were registered, with locations or volumes of failures that partially or totally involved the pre-existing landslide perimeter available in the latest release of the IFFI catalogue  without any fringes. This systematic approach allowed us to count intermittent reactivations for some of the mapped landslides over both preseismic and postseismic years.26. The dimension of the fishnet density was selected based on the frequency distribution of the landslide polygon areas in the catalogue; a compromise between the fishnet resolution and the median size of the landslide, enveloping areas able to preserve the unique entity of a landslide polygon, was adopted.To quantify the spatial distribution over time of the landslide reactivations, the density of EqTLs was derived over a regular square 1.5 km fishnet centred at the epicentral location; this method was previously adopted in Martino et al.The density of reactivations in the fishnet Fig.  was calcFor morphometric and landslide distribution analysis, a 20 × 20 m DEM distributed by the Italian Ministry of Environment covering the entire Molise Region was adopted.76 were reconstructed along and normal to the fault direction. A swath strip width of 10 km was adopted to include 95% of the landslide reactivations that occurred in the area.For the EqTLs Fig. , variatiSupplementary Information.


NOD-like receptors (NLRs) are intracellular sensors of the innate immune system that recognize intracellular pathogen-associated molecular patterns (PAMPs) and danger-associated molecular patterns (DAMPs). Little information exists regarding the incidence of positive selection in the evolution of NLRs of birds or the structural differences between bird and mammal NLRs. Evidence of positive selection was identified in four avian NLRs  using the maximum likelihood approach. These NLRs are under different selection pressures which is indicative of different evolution patterns. Analysis of these NLRs showed a lower percentage of codons under positive selection in the LRR domain than seen in the studies of Toll-like receptors (TLRs), suggesting that the LRR domain evolves differently between NLRs and TLRs. Modeling of human, chicken, mammalian, and avian ancestral NLRs revealed the existence of variable evolution patterns in protein structure that may be adaptively driven. Nod-like receptors (NLRs) are pivotal sensor proteins of the innate immune system with diverse functions. They detect pathogen-associated molecular patterns (PAMPS) of invading microbes and danger-associated molecular patterns (DAMPs), thus initiating an innate immune response.Structurally, members of the NLR family share a similar tripartite domain organization: a variable N-terminal domain, a central nucleotide-binding and oligomerization domain (NACHT), and a C-terminal domain .NLRs are grouped into subfamilies based on their specific N-terminal protein-protein interaction domain: the caspase recruitment domain (CARD), the pyrin domain (PYD), the baculovirus inhibitor of apoptosis protein repeat (BIR) domain, or an acidic transactivation domain , 2. ThesκB) and the mitogen activated protein kinase (MAPK) signaling pathway, or act as transcriptional regulators [NLRs detect PAMPS via a C-terminal leucine-rich repeats (LRR), which is a 20-29 residue repeated sequence with conserved and characteristically spaced hydrophobic residues . Recentlgulators , 13.Hydra, which have large and complex NLR repertoires, NLRs recruit downstream adaptor molecules after activation. These NLRs, with the associated adaptor proteins, may induce apoptosis or activate putative NF-κB/JNK transcription factors, thus regulating downstream cell responses and the expression of antimicrobial peptide [Hydra and many other animals, indicating that NLRs have evolved in a species-specific manner to adapt to various ecological niches [Most studies on NLRs have focused on NLRs of mammals and fish. Recent studies on NLRs of early diverging organisms have suggested adaptive evolution in NLRs. In  peptide . It has  peptide . Gene exl niches , 15.Xenopus and zebrafish, has been identified in chickens [Hydra and corals, to fish, birds, and mammals, have evolved in response to environmental conditions.In recent years, several important structures and functions of NLRs have been discovered in mammals. However, due to the different environmental conditions and ecological niches occupied by mammals and birds, conceivably their NLRs have evolved differently, generating unique structural and functional properties. Although evolution of the NOD subfamily of NLRs is known to be conserved in mammals, NOD2 is missing in chickens. In mammals, NOD2 senses specific bacterial muramyl dipeptides (MDP). In contrast to NOD2 in mammals, MDP are recognized by NLRP3 in chickens, suggesting that chicken NLRP3 replaces the role of mammalian NOD2 . In mammchickens . CollectThe aim of this work was, therefore, to identify evidence of positive selection in avian NLRs, to examine the structural and functional evolution of NLRs in birds, and to further elaborate the structural and functional diversity of NLRs between mammals and birds. Using Maximum Likelihood method, evidences of long-term selective pressure in the NLR genes have been found. To better understand how the CARD-binding properties of NLRs structurally and functionally diversified, ancestral NLR proteins were reconstructed and the structures of ancestral CARDs compared. Data from this study may provide more evidence for the role of positive selection in the evolution of NLRs.Our study identified some positive selection sites in the pathogen recognition domains of NLRs that were examined. To evaluate the functional significance of the inferred positively selected sites, the location for each putatively positive site has been summarized in supplementary materials Table . Our resGallus and human sequences  [The highest accumulation of positively selected sites was observed in the LRR region of NLRC5 . NLRC5 crch.com)  was usedrch.com) , 30, 31.Gallus NOD1 as well as for reconstructed ancestral NOD1 proteins  have been found within the functional domains. Amino acids 93 and 359 were located within the CARD domain and NACHT domain of avian NOD1, respectively. In the avian NOD1, Cys93 was replaced by Tyr, His, Arg, Leu, Phe, and Ser. Because the crystal structure of the human NOD1 CARD has been resolved and residues involved in the downstream signaling and interaction with RIP2 are recognized , we aligproteins . The resIt has been reported that NLRC3, together with NOD1, originated from a gene duplication event that occurred before the divergence of birds and mammals . A minimEvidence of positive selection in the bird NLRs is reported in this study with variable quantity and distribution of positively selected residues.κB pathway by recruiting the protein receptor-interacting protein 2 (RIP2) through the interaction of CARDs. Two positively selected codons have been found in the functional domain of the Gallus NOD1, amino acids 93 and 359. Interactions between NOD1 and RIP2 mainly depend on electrostatic interactions in the CARD domain [NOD1 is a crucial molecule in innate immunity. It activates the NF-D domain . The CARIn NOD1, the CARD domain is indispensable for downstream signaling, involved in many different cellular processes, such as apoptosis and inflammation. Because of functional constraints, residues with critical functions may be under slow evolutionary rate . It has α5) has the potential to influence the function of the CARD, we predicted the ancestral amino acid state of the CARD for mammals and birds and analyzed its 3D structure. The CARD domain of human NOD1 consists of six antiparallel α-helices packed around a hydrophobic core with residues E53, D54, and E56 of α3 involved in the interaction with RIP2 [To have further insight of the functional evolution of the NOD1 CARD and to understand if the positively selected residue  being the absence of α3, which was replaced with an α2-α4 loop. Interestingly, other studies of NOD1 CARD have suggested conserved α2 and α3 domains which form a putative interaction surface with the CARD of binding partner [α2 and α3 of CARD domains in NOD1 (positive selection 93 codon is in CARD α5 of NOD1). NLRC5, however, also contacts with the binding partner by CARD-CARD interaction and contains four positively selected sites that fall in the α2, α4, and α2-α4 loop of atypical CARD domain  was missing in the CARDs of bird NLRC5s . Sequencγ–inducible nuclear protein recognized as an important molecule for the MHC class-I antigen presentation pathway in humans [NLRC5 is an IFN-n humans , 18, 24.n humans , 18. Mutn humans  and thern humans . It has,n humans . In zebrn humans . These fκB through interaction with TRAF6 [κB pathway by binding with TRAF6 [A minimal number of adaptive substitutions have been found within NLRC3 , which falls in the region closest to the C-terminal LRRs. Because of the large size of the LRR region and unusual structure of NLRC5, it has been speculated that NLRC5 might sense different stimuli, compared to other NLRs . Some ofThe Nod-like receptors of the innate immunity represent the first line of defense against the pathogens. These are involved in pathogen recognition and, thus, need to evolve rapidly in a dynamic arms race with pathogens. Evidence of positive selection of NLRs in birds has been observed. Adaptive selection in avian NLRs was different than either avian TLRs or mammalian NLRs. NLRs have shown adaptive divergence in structure and function throughout the avian evolution. This work provides a basic understanding of structural and functional evolution in avian NLRs. By looking for structural differences between human, chicken, mammalian ancestral, and avian ancestral NLRs, we propose that the different environmental conditions encountered by mammals and birds might have induced structural and functional differentiation among members of the NLR family. Different NLRs with varied functions might have experienced unique pressures which might have induced the evolutionary change.http://www.ncbi.nlm.nih.gov). NOD-like-receptor amino acid sequences of chicken, avian ancestors, and mammalian ancestors are displayed in supplementary materials The coding regions of three chicken (Lingnanhuang: LNH) NOD-like-receptor genes, NOD1, NLRC3, and NLRP3, were obtained by polymerase chain reaction (PCR) amplification using gene-specific primers  [http://nls-mapper.iab.keio.ac.jp/cgi-bin/NLS_Mapper_form.cgi) [Sequence alignments were produced using PROBCONS version 1.12 . The alisu.edu/) . All anaorm.cgi) .http://www.datamonkey.org) [p value =0.1 for SLAC and FEL and Bayes Factor = 50 for REL analysis, sites with a p value <0.1 for SLAC and FEL, and Bayes Factor > 50 for REL was accepted to identify candidates for selection.All sequences for testing positive selections have been displayed in supplementary materials key.org) . For codkey.org) . In HyPhProtein-coding substitutions identified as more than or equal to two ML methods were considered adaptive. In order to identify robust sites under positive selection, only sites with evidence of selection in at least two of the ML methods were considered. In addition, the PAL2NAL program  was usedAncestral protein sequences were reconstructed using MEGA 6  with thehttp://nbcr-222.ucsd.edu/pdb2pqr_2.0.0/) [To obtain a more precise idea of the functional evolution of avian NLRs, structural homology models are built with MODELLER v9.5 . Then, t_2.0.0/)  to add h_2.0.0/) .


Sports management is booming, thanks to society’s growing interest in sports in general. This work provides an exhaustive review of the scientific literature of one of the variables most coveted by managers: loyalty. Antecedents positively related to loyalty are also conceptualized in this paper. The scientific literature search was limited to the last 15years to achieve a better fit with today’s context. The Web of Science database was the main search method used, along with other, secondary resources, for a total of 328 scientific articles obtained as a base for this review. The results of this study bring together the most representative data in a systematic review of the loyalty variable in the field of sports management: the antecedents of loyalty, the terms with the greatest presence in the theory, the most representative authors and sources of this topic, and so on. One of the most significant results obtained from the review of these 300 bibliographical references is that the factors to be borne in mind for marketing strategies in sports organizations are satisfaction, commitment, trust, and service quality. The literature reflects that these variables, present in studies on loyalty in general, can also be found in the literature on sports management – in particular, satisfaction and service quality. However, few papers include all these antecedents at once, making this an interesting field for future research. Loyalty is one of the principal objectives of marketing and is sometimes even equated to the concept of marketing itself . LoyaltyThe sports industry generates billions of dollars; a better understanding of the relationship between the product and its consumers is thus a key factor for the marketing managers of sport organizations. Maintaining relationships over time, independently of whatever factors may arise, is also of key importance. Loyalty therefore becomes a crucial element in maintaining relationships over time and thus an element on which marketing managers must focus .Sport organizations include all those bodies that pursue sports-related activities. They may therefore be companies that offer goods , services , ideas , or a combination of all of these . The waySports products have unique aspects that affect the basic conditions for selling them: they are products that are inherently uncertain; they are inconsistent and open to subjective interpretations; they take place under highly competitive conditions; and marketing managers for these products do not have full control over the marketing mix . It is aConsumer loyalty is an asset highly valued by all types of organizations and directing available resources toward improving loyalty is much easier if this concept has been analyzed. This work aims to examine the existing literature on loyalty to a sports organization and verify whether the variables that explain loyalty in organizations in general are also present in sports theory. On this basis, the following questions are raised:Q1: Does loyalty to sports organizations behave in the same way as consumer loyalty to any other organizations?Q2: Is the quality of sports services a key variable for consumer loyalty?Q3: Is satisfaction the most representative variable of sports consumer loyalty?Q4: Can commitment and trust variables explain loyalty in sports?The following sections aim to offer an exhaustive review of loyalty from the point of view of sports management considering the main antecedents that lead to loyalty in sports organizations. In a first step, the different loyalty concepts and their main antecedents  are analyzed. Then the various sources used are detailed, as well as the main search criteria. The results presented compile the most notable data on the bibliography related to sports loyalty, through a systematic analysis of the literature, while the paper ends with the main conclusions derived from this search.Loyalty has been conceptualized by various authors in the fields of both psychology and marketing. Many authors have made in-depth studies of this concept from the marketing perspective, and all agree that loyalty comprises all those behaviors involving same-brand purchasing repeatedly, both now and in the future , despiteLoyalty is made up of two concepts, which combine to give the variable the greatest explanatory power. These two concepts are: behavioral aspects or purchase intentions and attitudinal loyalty . BehavioBy focusing on loyalty in the field studied in this paper, i.e., sport, it becomes clear that it is more difficult to conceptualize loyalty when the subject is services than when discussing products. This is partly because, in the case of services, it is impossible to separate the consumer from the person providing the service, and this participation by the client in the interpersonal component of services – their production and delivery – adds emotional dimensions to loyalty . The indIn recent decades, the literature on loyalty has multiplied and we have found many studies that aim to explain it see . These iThis variable is defined as the discrepancy between a consumer’s prior expectations for a given service and his or her perception regarding the purchase or services . This imGeneral satisfaction is a general assessment based on all the purchases and the consumers’ experience of using a product or service . AnotherCommitment is understood to be the implicit or explicit promise of a long-term relationship between the parties . SimplifMany authors agree that trust is one of the basic ingredients for success in relationships . Trust iFollowing other examples , a systeLoyalty has been a highly studied concept in different areas, that is why the search criteria used have been very specific. Using key words like “loyalty and sport,” “loyalty and sport management,” “loyalty and satisfaction in sport management,” “loyalty and service quality in sport management,” “loyalty and commitment in sport management,” and “loyalty and trust in sport management.” Satisfaction, service quality, commitment, and trust were included in the search criterion because they are the main variables that affect to loyalty in a general context. The search time range covered the last 15years, from 2006 to 2021. During that period, sport has experienced significant growth – as have all related sectors – and competition between organizations is getting increasingly strong, leading in turn to an increased need to retain the consumer .Some 1,154 articles were compiled in the identification phase. These were subsequently reduced to 599 once duplicate articles were eliminated. Several refining phases followed, with the analysis of the abstracts and the keywords included in each article.In a first step, all those articles not specific to the sports sector were excluded, leaving the database with 438 articles. In a second exclusion phase, all those articles that did not measure the loyalty variable were rejected: 328 articles remained. The selection, classification, and exclusion phases were carried out using an Excel file. In the following section, the data extracted – mainly from the WoS – are presented.The results of this review indicate that there are various authors who have vast expertise in sports loyalty. There are numerous magazines that focus on sports and sports management. Moreover, articles on sports loyalty are also published in other journals, such as those with a more general focus or in other specific fields such as tourism or the internet. The magazines that publish the most articles on the subject studied are mainly magazines specific to sports management. In the literature there are different terms related to loyalty that appear in some of the most accepted definitions of loyalty in the theory, although such definitions differ. An example is the term “purchase intentions” defined in loyalty as the intention to buy from the same organization continuously over time .Another term that can be linked to loyalty is “resistance to change,” since this concept appears in various definitions of loyalty .Resistance to change was a more common term in the literature than loyalty; however, in recent years loyalty has become much more popular, surpassing resistance to change.Without any doubt, the term most used in theory is “behavior intentions,” followed closely by “consumption behavior.” Nevertheless, these two terms are much more general than loyalty and resistance to change, since they include loyalty and other variables such as word of mouth. . In addiIt is undoubtedly true that all types of sports organizations aspire to gain the loyalty of sports consumers. The literature includes various examples of the variables that explain this loyalty. The most common loyalty antecedents in the general literature are satisfaction, quality of service, commitment, and trust. The question is whether this also occurs in the literature on loyalty in sport.Satisfaction is the variable most present in the literature on loyalty in the sports field. Another of the variables that has been most associated with loyalty is service quality. Although the variables most found in the literature on loyalty in sport are satisfaction and service quality, the articles with the most citations do not study these variables, focusing instead on commitment and trust.In total, there are 328 articles on loyalty in sport, of which five are those that study the four variables analyzed in this paper: satisfaction, service quality, commitment, and trust. The loyalty variable has always been extensively researched in the field of literature of business field and more specifically in the sports field. Indeed, there is so much literature associated with loyalty in the field of sports management that it can be very difficult to navigate. The purpose of this paper, then, is to use a systematic review of more than 300 references to identify and classify the most relevant information on this topic and review the different factors and variables that define loyalty in sports management. Finally, it aims to check if these variables coincide with the most common variables in loyalty in general. This in turn requires an in-depth study of the variables that influence the loyalty.Satisfaction is a crucial element of consumer loyalty; most studies that model loyalty include satisfaction as an explanatory variable, and, in practically, all cases they demonstrate its positive influence . DespiteThe variables commitment and trust are much less present in the literature on loyalty in sports management than in other sectors such as the workplace. However, they cannot be ignored since articles that include these two variables in relation to loyalty have the best citation ratios: a very good indicator of the quality of these works. These two variables are definitely related to each other  and are The country that produces the most publications on loyalty and sports management is the United States, which has 92 articles. This can logically be expected, since the United States is one of the countries that produces the most publications in general. In addition, many sports management magazines are from the United States, which favors the proliferation of works on these topics from that country.It is curious that the second country with the most articles is Spain, since this country does not have the base and structure of resources that the United States has. This indicates the great interest in sport among Spanish researchers, as well as the specialization of the country’s experts in these variables.Daniel C. Funk could be considered as one of the greatest experts in sports management since he has published dozens of articles on this subject. According to the results of this study, he is also the author with the most published works on loyalty in the field of sport. Furthermore, he is the author with the most citations, which certifies the quality of his work. All the authors that appear in the list of results are major experts on the subject, since having more than seven publications on a specific topic is a sign of their knowledge on the subject. It is worth highlighting two authors: Heath McDonald, who appears in the top five for both number of publications and number of citations; and the Spaniard Jerónimo García-Fernández (eight articles), who appears in the top five for number of publications. He is likely to be one of the main reasons for Spain ranking second worldwide in number of publications.Another conclusion derived from the results presented in this literature review is about the type of journals that publish on these topics. Unsurprisingly, focusing on specific sports management sources is the best option, since they are the ones that publish the most about loyalty in sport. However, other journals that may approach this topic and that may include call for papers on sports management should not be disregarded, even though sports management is not their main focus.The subject selected for this systematic analysis of the literature has a wide variety of works. Sport generates great interest in society and therefore in the scientific community as well. This work attempts to order and classify the theory on loyalty and sports management and identify the main shortcomings of the scientific literature on this topic.The loyalty antecedents analyzed in this work have a strong presence in the theory; however, there are very few articles that present all the variables. From 328 articles found, only five consider satisfaction, service quality, commitment, and trust. Therefore, the approach of models that explain loyalty in the sports field offer an excellent starting point for continued research into this variable.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.All authors contributed to conception and design of the research, reviewed the theorical background, organized the database, performed the bibliometric analysis, wrote all the sections of the manuscript, contributed to manuscript revision, read, and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Mining is a high-risk industry and a crucial economic driver that has a crucial role in the economies of countries worldwide. The implications of the labor market on the sustainability of the mining industry have increased the importance of sustainable human resource management at the strategic level of mining and safety management. In this article, from the perspective of management research in an energy production enterprise, we investigated the relationship between employee loyalty and employee satisfaction through a survey that targets employee loyalty, work quality, and job satisfaction and the relationship between enterprise image and switching costs. Based on service profit chain theory, we established a research model for mining employee loyalty, and 500 miners in a typical extreme mining environment in China were surveyed. The study hypotheses were tested using a structural equation model and an employee loyalty model, followed by empirical testing of the models. Employee loyalty was significantly associated with enterprise image and employee satisfaction, work quality indirectly affected loyalty through satisfaction, and the impact of switching costs on employee loyalty was not significant. We provide strong empirical evidence to help enterprises improve sustainable human resource management and regulatory policies, with important implications for safety production. Our study also provides a useful reference for further studies of sustainable human resource management in mining. Despite extensive efforts to improve mine safety, accidents still pose a threat to the sustainability of the mining industry, as they can lead to the death and injury of workers, property degradation and environmental damage2. According to statistics5, the main causes of accidents are violation of operating rules or labor discipline and poor production environment. Ninety-seven percent of mine accidents are caused by miners' unsafe behaviors7.Mining is a high-risk industry that plays a crucial role in the economy in countries around the world10. Since people's attitudes are always reflected in their behaviors, behaviors are most likely determined by attitudes. The relationship among a contractor's risk perception, attitude and behavior has been analyzed11. Zohar and Luria12 believed that the security climate was a subset of organizational climate, and employees' behaviors were shaped by their expectations of organizational value and the reward system. Mohamed13 used a structural equation model (SEM) to study the relationship between safe climate and safe work in a construction site environment and proved that safe work behavior is the result of a safe climate. The social communication between workers and managers on organizational safety is considered important14. In discussing social exchange theory, it is believed that when one party behaves in a way that provides benefits to another party, an implied obligation for future reciprocity is created. Therefore, psychological contract theory is considered the result of social exchange theory, which can be considered in exploring the relationship and different motivations between managers and workers in terms of safety15. Intrinsic characteristics can strengthen the loyalty relationship between workers and managers16. It was found that employee loyalty was positively correlated with labor productivity17. They thus proposed management policies and countermeasures to improve employees' loyalty to the organization. When organizations fail to meet individual expectations, the employee turnover rate in the construction industry will increase, which will lead to the collapse of the employment relationship and thus facilitate accidents18. Therefore, construction units should establish the understanding and management mechanism of employees' psychological contracts and develop employee incentive schemes to enhance employees' loyalty to the organization. Some studies have confirmed the mediating effect between loyalty factors and satisfaction. Othman19 quantified the drivers of customer loyalty and satisfaction through an international questionnaire and took satisfaction as an intermediary variable to express employee loyalty. In high-risk industries, such as mining, previous studies have focused on unsafe employee behavior, accident causes and the relationship between accidents and people's behaviors, but very few studies have paid attention to the interaction between employee satisfaction and loyalty in relation to accidents. Therefore, this study mainly investigated the interrelationship among employee image, switching cost, work quality , employee satisfaction and loyalty in the high-risk mining industry and establishes a loyalty conceptual model. It provides new ideas and theoretical support for safety management decisions and dynamic management in mining enterprises.With the deepening of the related research, multi-perspective analysis and research on unsafe behaviors and safety management have been carried out in many industries. Human error is defined as the failure of planned actions to achieve the expected goals, although human error is a major cause of unsafe behavior in accidents20. Sustainable HRM can help mining enterprises attract and retain high-quality employees, improve the management of employees and reduce unsafe behaviors to ensure production safety22. Therefore, it is urgent to study employee satisfaction and loyalty as important factors of sustainable HRM.However, sustainable human resource management (HRM) can help mining enterprises establish an attractive enterprise brand that can address the different needs and expectations of potential and existing employees without damaging long-term corporate image, thus promoting sustained competitive advantageIn this study, we investigated employee satisfaction and loyalty in the largest copper mine in China (Pulang Copper Mine). These interviewees are suitable for this study due to their strong industry representation. The main reasons are as follows. First, this mine is the largest copper mine production enterprise in China, and a series of face-to-face conversations with managers and miners indicate that there are a large number of miners in this mine with high mobility. Second, our conversation with the miners before the questionnaire survey showed that they were concerned about the safety management of the mine and had a good understanding of the safety production issues. A literature review revealed that research on the loyalty of miners in plateau mines is lacking, so this study comprises an exploratory study. Regarding the framework of this model, previous studies applied employee satisfaction as a single component to investigate the mediating effect of employee loyalty, while this study considered satisfaction a key component according to the characteristics of mine employees to identify specific relationships of employee loyalty and to describe how these relationships affect employee loyalty. This study closes the research gap and contributes important knowledge to current research on the loyalty of miners and mine safety management in plateau mines. However, the intention of this paper is to examine the psychological changes and influencing factors of job satisfaction and loyalty of mining employees in high-altitude and working conditions in environmentally challenging environments.The research framework of this paper is described as follows: First, we reviewed the relevant literature and defined the concepts of employee satisfaction and loyalty to provide a theoretical basis for the study. The influencing factors of employee satisfaction and the relationship between these factors and employee satisfaction and loyalty were described, as was the relationship between employee satisfaction and employee loyalty. Second, on the basis of previous studies, the concept of the employee loyalty hypothesis model is proposed. The SEM based on variables and Amos software were used to test the hypotheses. Then, the results were evaluated, discussed and summarized. Finally, the research implications, limitations and directions for future research were presented in the conclusion.23. Employee satisfaction also includes a comparison of future expectations of one's own work and external future opportunities24. Employee satisfaction is considered to be the overall feeling about a job or the attitude towards the job25. Rice et al.26 proposed that satisfaction was to some extent determined by the differences generated in the process of psychological comparison, which involved the assessment of current work experience according to an individual’s comparison criteria. Employee satisfaction is defined as the pleasant or positive emotional state generated by the evaluation of a job or work experience27.Employee satisfaction is defined as an index of preference for experienced work, while preference for external opportunities depends on the information available at a given time28.However, employee satisfaction is an extremely important variable that can reflect the general mood and thinking of employees about the nature of work and the working environment and conditions. Therefore, employee satisfaction refers to employees' expectations of the workplace and attitude towards work and psychologically determines their work behavior ability and risk perception. Thus, job satisfaction is a function of one's needs being met to some extent29. Factors that lead to job satisfaction are called motivators and include achievement, recognition, the job itself, responsibility and promotion. The factors that prevent job satisfaction and lead to job dissatisfaction are called hygiene factors and include administrative policies, supervision, remuneration, interpersonal relationships and working conditions and quality30. Moreover, the impact of employee satisfaction has been analyzed considering five factors, namely, empowerment and participation, working conditions, rewards and recognition, teamwork and training, and personal development31.Scholars have put forward many theories about the definition of employee job satisfaction. For example, motivation-hygiene theory states that the factors that create job satisfaction are separate from those that lead to job dissatisfaction32.Employee loyalty refers to employees having deep feelings for the enterprise, being willing to collectively grow with the enterprise, having a sense of responsibility and mission in work, contributing their intelligence and wisdom to achieve the enterprise's goals, and fulfilling their role in helping the enterprise to achieve its strategic goals33 proposed that employee loyalty refers to employees' recognition of the enterprise and their attitude and behavior of performing their best, which is embodied in their consistency with enterprise values and policies in ideology.Zhao and Li34. Since employee loyalty and enterprise loyalty have an interactive relationship, employee loyalty originates from the enterprise loyalty to employees34. Therefore, loyalty is characterized by a strong desire to remain a member of the organization, which plays a positive role in retaining members of the organization.Employee loyalty refers to the degree of employee loyalty to the enterprise, which is a quantitative concept. Enterprise loyalty means that the enterprise creates an acceptable corporate culture and environment for its employees and provides them with development opportunities and material rewards, so that they can devote themselves wholeheartedly to their work and integrate their personal development into the development of the enterpriseAll the above researchers acknowledge that employee loyalty plays an important role in enterprise development. In general, loyalty mainly includes behavioral loyalty theory, attitudinal loyalty theory and synthesis theory. This paper adopts the abovementioned theories to investigate the loyalty of miners in the mining industry. Especially in the plateau mine, the environment is poor and the working conditions are more complex, which causes the loss of a large number of miners and technicians and creates severe challenges to production safety management. The paper attempts to research the influencing factors of miners' loyalty. This research is helpful for plateau mine managers who wish to master the psychological contract of miners, which is critical to mine management decision-making and sustainable human resource management.In 1994, a service management research group composed of James L. Heskett and W. Earl Sasser. Jr and other professors of Harvard Business School proposed the "service profit chain" model. Service profit chain theory holds that there is a direct correlation between employee satisfaction, employee loyalty, employee work quality and efficiency, customer value, customer satisfaction, customer loyalty, and enterprise profit and growth. According to the theory and the special situation of the mining industry, this paper constructs the research concept hypothesis model.Employee work quality drives employee satisfaction. The factors that make employees satisfied with an enterprise generally include two aspects: first, the external work quality provided by the enterprise, such as salary, welfare, comfortable working environment and other external conditions that can be seen; second, the quality of internal work provided by the enterprise, including the selection and development of employees, reward and recognition, information access channels and work design, organizational leadership and other aspects.35. This study investigates four aspects of work quality . Most studies indicate that employee satisfaction is mostly based on work quality. Host and Knie-anderson36 noted that reliability and certainty can predict satisfaction in five aspects of job quality. However, Parasuraman et al.37 believed that improving work quality can help build employee loyalty, and work quality has a positive impact on employee loyalty. Although the above studies support the positive relationship between job quality and employee loyalty, most studies have found that the direct relationship is not significant39 because the relationship between work quality and employee loyalty is affected by the mediating variable of employee satisfaction. Therefore, the following hypothesis is drawn in this study.Employee work quality refers to the employee's evaluation of the overall superiority of working conditions and psychological contract satisfaction, which is a cognitive qualityWork quality has a positive effect on employee satisfaction.40. Liu et al.41 believe that enterprise image is the overall impression of an enterprise among the public. Based on the above research, it can be seen that enterprise image is the overall cognition of an enterprise among employees, which represents the degree of employees' identification with the enterprise. However, an enterprise image has a significant impact on employee loyalty and has a key role in employee retention42, and A positive enterprise image has a positive effect on employee loyalty43. Therefore, enterprise image may be positively correlated with employee satisfaction and loyalty. The following hypotheses are proposed:Enterprise image refers to the overall impression of the enterprise among employees. The enterprise image exists in the hearts of employees and drives their intention of employment in the enterprise. The formation of enterprise image is the visibility of the enterprise to society and the subjective overall evaluation of the internal management and production conditions in the minds of employees. A good enterprise image can improve employees' satisfaction and identification with the companyThere is a significant positive correlation between enterprise image and employee satisfaction.There is a significant positive correlation between enterprise image and employee loyalty.44. When employees' switching costs increase, their sensitivity to satisfaction will decrease45. A large number of studies have pointed out that the switching cost perceived by employees is an important factor in employee loyalty44. Dissatisfied employees may stay in their old companies simply because they would have to spend extra time and effort to change companies, which is costly. Therefore, the switching cost has a significant impact on employee satisfaction and loyalty. The following hypotheses are proposed:Switching cost is an important reference factor for employees considering switching companies. When employees consider changing careers, they measure the costs and benefits of the change, and if the price of switching is higher than the benefit, i.e., if the switching cost is too high, exit barriers can be formed, making employee conversion less likelyThere is a significant positive correlation between switching cost and employee satisfaction.There is a significant positive correlation between switching cost and employee loyalty.46. However, these management drivers influence employee loyalty through satisfaction. In terms of the impact of management drivers, satisfaction is regarded as an endogenous variable, but in terms of the impact on employee loyalty, satisfaction is also an exogenous variable16. Therefore, according to the identification of the variable coefficient of the mediation variable47, satisfaction is considered the mediator of the model. Turkyilmaz et al.28 and Matzler et al.48 reported a significant mediating effect of employee satisfaction on employee loyalty. Employee job satisfaction has a positive impact on employee organizational loyalty49. According to Martensen and Gronholdt50, employee satisfaction is positively correlated with employee loyalty. In addition, a consistently strong relationship between organizational loyalty and the job satisfaction of employees has been reported51. Employee job satisfaction is positively correlated with loyalty. Therefore, the following hypothesis is proposed.In empirical studies, satisfaction is a prerequisite for loyaltyThere is a significant positive correlation between employee satisfaction and employee loyalty.According to these hypotheses, a model was constructed, and the research framework developed in this study is shown in Fig. 54; the dimension of work quality scale is derived from Parasuraman39 and Hong et al.55; and the dimension of employee satisfaction scale was adapted from Ibanez et al.39, Liu et al.41, Anderson et al.56 and Zhang57. The measurement of enterprise image was adapted from the literature of Nguyen and LeBlanc58, Chang and Tu42 and Liu et al.41. Finally, the switching cost dimension scale was adapted from Jones et al.44, Fornell59 and Kim et al.60.In the structural model of this study, all structural measurement items were adapted from the literature  to 7 (strongly agree) for all variables to measure the construct items63.To test the proposed model, a double translation protocol was utilized to develop the questionnaire47. First, the missing values were excluded from the dataset. Second, the skewness index (SI) and kurtosis index (KI) were used to test the normality hypothesis of each index distribution. The SI reported in this study was between − 1.692 and − 0.699, and its absolute value was less than the recommended level of 347. The KI values ranged from − 0.466 to 3.958, and the absolute value was less than 1047. Therefore, the normality assumption of these indicators was not rejected16.Prior to SEM analysis, the raw data were filtered to identify possible problemsThe research object of this paper is the miners of Pulang Copper Mine, which is the largest copper mine in China. It is located in southwest China at an altitude of 3500–4000 m, and the temperature is − 5 ~ − 20 °C. In this study, face-to-face questionnaires were employed. The data were collected over three weeks in the winter of 2019. Stratified random sampling was performed in this study according to the working characteristics of each miner and the number of miners in the whole mine. In total, 200 surface miners, 250 underground miners and 50 surface managers were selected as the survey samples. Hence, a total of 500 questionnaires were distributed during the period, and 478 questionnaires were collected with a recovery rate of 95.6%. After the elimination of incomplete and invalid questionnaires, 440 useful responses were obtained for data analysis, with an effective rate of 92.1%. Among the respondents returning valid questionnaires, the sample was mostly male (91.3%) and mostly 30–39 years old (68.5%). Most of the respondents had 5–10 years (78.6%) of working experience in their current company.This study was approved by the Research Ethics Committee of Northeastern University (23-2019-0105). All methods were carried out in accordance with relevant guidelines and regulations. Informed consent was obtained from all subjects following a detailed explanation of the study objectives and protocol to each subject. All subjects provided written informed consent prior to being monitored.64. Pearson correlation analysis was used to verify the correlations between study variables. The relationships between demographic factors, factors related to miners' satisfaction and loyalty factors were used to predict miners' psychological status, and path analysis (SEM-maximum likelihood estimation) was used to test the model with a significance level of p < 0.05, p < 0.01 and p < 0.001. SEM is a multivariable technique that follows a conceptual model, path analysis diagram and relational regression equation system65. The SEM is a comprehensive statistical method for testing hypotheses about the relationship between observed variables and potential variables. The SEM combines the characteristics of factor analysis and multiple regression to analyze the measure and structure of a theoretical model. The SEM is formally defined by two sets of linear equations: inner model and outer model. The inner model specifies the relationship between two unobserved or potential variables, while the outer model specifies the relationship between the potential variables and their associated observed or display variables66.©IBM SPSS 22.0 and ©IBM SPSS AMOS 24.0 were used for statistical analyses in this paper. Basic descriptive analysis was performed to obtain scores for the five dimensions of the questionnaire, and descriptive statistics  were calculated54. Cronbach’s alpha was used for the reliability test. Cronbach's alpha is a measure of the reliability of a scale or test that overcomes the disadvantage of partial splitting. Cronbach’s alpha is the most commonly employed reliability analysis method in social science research. In basic research, the reliability measure coefficients of all components exceeded the threshold value of 0.7067, and each measurement remained above the values of 3 explanatory variables to achieve a correctly identified or overidentified model. Validity refers to the accuracy of the measurement. The purpose of principal component analysis is to find the most meaningful basis and express the similarities and differences in the data. In addition, confirmatory factor analysis (CFA) is a way to test how well a variable represents the construct. CFA verification results can provide evidence for the convergence and discriminant validity of theoretical constructs68. In this paper, the higher-order mediation model is involved. Previous studies have shown that the advantage of using the second-order factor model in SEM is mainly to simplify the model and program for easy interpretation69. The target coefficient (first-order measurement model χ2/second-order measurement model χ2) is a method to measure the second-order model. The target coefficient (T) is close to one, indicating that the second-order model is more representative. However, when T is 0.74, it is acceptable70. For example, work quality in this paper is a multidimensional structure with second-order latent variables in four structures: comfortability, reliability, responsiveness and empathy. To measure second-order factors, first-order factors are used as dependent variables71. Regarding the square root of the latent variable average variance extraction (AVE), to obtain sufficient discriminant validity, the square root of any potential variable’s AVE should be greater than the correlation between it and other potential variables72.In this paper, reliability and validity tests were used to examine the five latent variables and their constructs. First, the reliability of each construct was tested. Reliability represents the variance of a measurement resulting from repeated measurements of the same concept. It is related to nonsystematic errors and can be expressed as stability, consistency, predictability and accuracy73. This value can be calculated using standardized loadings:73. The average variance extracted was calculated as follows:Reliability is an indicator of convergent validity, and we assessed the latent factors’ reliability by calculating a composite reliability for each construct2), root mean square error approximation (RMSEA) and goodness-of-fit index (GFI)), incremental fitting (adjusted goodness-of-fit index (AGFI), comparative fit index (CFI), Tucker- Lewis index (TLI), normed fit index (NFI)), and parsimonious fitting (Chi-square/degree of freedom (df))72. Holms-Smith et al.74 and Hair et al.75 suggest using at least one fitness index for each model fit category. Chi-square/df should fall between 1 and 5; the CFI should be greater than 0.90; the standardized root mean square residual (SRMR) should be less than 0.08; and the RMSEA should be less than 0.0676. Chi-square/df, GFI, AGFI, CFI and RMSEA were used as the measurements of model fitting in the analysis of this study.Model fitting can be divided into three categories: absolute fitting . However, the correlation values did not exceed the cutoff of 0.90, indicating that there was no multicollinearity problem between items77. The study adopted a subjective survey for measurement. However, the results may present the risk of common method variance16. Hence, we also used Harman's single-factor test to detect common method bias in the data78. By adding all the observations together and analyzing factors or components, the cumulative percentage of explanatory variation under the unrotated axis was 51.946%80. Therefore, common method bias was not evident.Table 81. When conducting SEM analysis, researchers usually evaluate the measurement model before discussing possible structural models. The measured variables accurately reflect the structure or factors. In general, problems with SEM are caused by measurement model problems that can be identified by CFA68. Therefore, AMOS was used for CFA, covariance matrix and maximum likelihood estimation. The results of the model include five factors and a total of 36 indicators. In the CFA measurement model shown in Fig. 82. However, as shown in Table P < 0.001).CFA plays a key role in measurement model verification in path or structure analysis75. Convergent validity can be estimated by factor loading and AVE. Discriminant validity refers to the degree of difference and evidence of excessive correlation between a factor and other constructs75. In the first-order factor model, the AVE is used to measure the degree of difference between each construct and other constructs. The mean variance of each structure is shown in Table 83. In addition, the square root of AVE is greater than the maximum correlation between constructs (the shared variance between the two constructs), indicating significant discriminant validity13. As shown in Table Next, the convergent validity and discriminant validity of the measurement model factors were tested. Convergent validity refers to the aggregation or sharing of a high proportion of variance in a certain dimension84 determined the fitness of the data by calculating the target coefficient (T) and comparing first-order and second-order CFA. A T value close to one indicates that second-order CFA can replace first-order CFA, making the model more precise and simplified85. The T value of work quality in this study is 0.940 , df = 286, χ2/df = 3.060, GFI = 0.869, AGFI = 0.839, CFI = 0.942, RMSEA = 0.069. Comparison of the results with the corresponding critical values showed that the conceptual model fit the empirical data well86. The critical values of model fitting are as follows: χ2/df below 5 is acceptable, GFI and AGFI are > 0.8, CFI value is > 0.9, and RMSEA is < 0.08 (less than 0.05 is better). Therefore, the model has satisfactory explanatory ability and robustness, as shown in Table 87.According to the research hypothesis, the model was tested through SEM analysis  and adjusting the system of safety management measures and psychological characteristics to adapt to the characteristics of the psychological contract, the safety and risk awareness of staff can be improved, errors can be reduced, personnel can be screened, and the occurrence of safety accidents can be curbed. This kind of security management thinking becomes particularly important. Therefore, the importance of the dynamic perception of employees' psychological status is widely recognized in most fields and a focus of enterprise institutional decision-making, especially in high-risk production industries.This paper empirically studies employee satisfaction and loyalty in a high-risk industry in an extreme environment. To clarify these relationships, a research model was proposed to analyze the relationships among five constructs. The model has six hypotheses, which were tested by using data collected from miners in China's largest metal mining company. The reliability and robustness of the model are verified, and the results are satisfactory.88. This finding is similar to those of previous studies90. Clearly, enterprise image and employee treatment are very important to improve employee loyalty and material satisfaction. Moreover, the enterprise image (H3: β = 0.383) has positive direct effects on employee loyalty by providing employees information regarding the recognition of the enterprise. Interestingly, the field investigation showed that switching costs (H5: β = 0.039) have no significant impact on employees' degree of loyalty because the mining enterprise is located in a remote area with few alternative employment options, which greatly limits employees’ career prospects. Therefore, employees are mostly forced to work at this company because the decision to resign and choose a new enterprise would be costly. The employees’ psychological characteristics lead them to continue working at the high-risk enterprise.The results show that enterprise image (H2: β = 0.226) and switching costs (H4: β = 0.189) have a positive impact on employee satisfaction , and the effect was very significant. Moreover, employee loyalty was positively correlated with work quality (H1: β = 0.603) and employee satisfaction (H6: β = 0.284) (refer to Figs. The research results are of great significance to mine safety management, especially for reducing unsafe behaviors on site and highlighting employees' dynamic psychological changes. Psychological contract theory and employee satisfaction and loyalty are applied in the context of safety behavior, and the key role of employee psychology in safety management is realized, which provides a new direction for mine safety research. Through the real-time investigation and study of this loyalty model, an enterprise can identify the psychological changes of short-term employees, grasp which safety systems and decision-making regulatory policies of the enterprise do not fully meet the requirements of workers, and carry out real-time improvement and optimization of safety systems.Academically, this study contributes in several ways. This study contributes to the empirical testing of the impact of work quality, enterprise image and switching costs on employee satisfaction and employee loyalty in extremely high-altitude and low-oxygen environments. Moreover, it seeks new safety management methods to effectively and safely improve production performance and enhance employee satisfaction and loyalty by improving work quality, for example, by optimizing the production process system, improving the treatment of employees to prevent brain drain, shaping a good enterprise image, improving work conditions, and improving employee satisfaction and loyalty. According to the questionnaire survey of miners' cognition of working environment conditions, enterprise image and their psychological dynamics of job satisfaction and loyalty, dynamic monitoring of miners' psychological changes during practical production was performed through this research model. The enterprise management mode and system were adjusted in real time. In addition, the model of this study is helpful for the practice of dynamic, real-time monitoring of mining employees' psychological dynamics as a reference for enterprise decision makers in safety management.This study has some limitations. A large amount of data were collected through questionnaires, and opinions were solicited from department leaders and front-line workers. The questionnaire survey, which was conducted in only one mine in one region, was not compared across multiple situations from a large diversity of locations and environments to reduce the chance that the results would be valid for only a single case. However, the models and data obtained are not universally applicable. Considering that a large number of employees participated in the data collection and that the level of knowledge varies greatly across employees, the interviewees may have offered vague judgments on some investigation factors. Therefore, it may not be possible to completely control the implementation of the questionnaire survey. In addition, this study mainly investigated the employees of mining enterprises in high-altitude and cold areas to establish an employee loyalty model. Hence, the universality of this research model may be limited.Future research should account for the above limitations. In the future, we plan to increase the data collection volume and expand the scope of the survey area. Moreover, we will extend the model to other employees through further survey research to improve the interpretation ability and general adaptability of the model. Another direction for future research would be to develop a more comprehensive computer-based sample collection technique to analyze the psychological security factors of employee loyalty in different industries or areas.This study quantitatively analyzed employee satisfaction and factors that affect employee loyalty in the high-risk mining industry in China. The findings of the study demonstrated the important characteristics of satisfaction as a driving factor and mediating variable with direct and indirect relationships with mine workers' loyalty. The results show that there is a linear positive correlation between employee satisfaction and employee loyalty in mining enterprises. Specifically, employee loyalty is significantly related to enterprise image and employee satisfaction. Work quality indirectly affects employee loyalty through satisfaction, while switching costs have no significant impact on employee loyalty. Accurate dynamic and real-time monitoring of the psychological dynamics of the employee satisfaction level and loyalty of workers in high-risk industries is very important for improving work quality and safety. We provide strong empirical evidence and conceptual models that can play an important role in improving sustainable HRM and operational performance as well as institutional decision-making regarding safety.