Abstract

Corporate bankruptcy and financial distress prediction is a topic of interest for a variety of stakeholders, including businesses, financial institutions, investors, regulatory bodies, auditors, and academics. Various statistical and artificial intelligence methodologies have been devised to produce more accurate predictions. As more researchers are now focusing on this growing field of interest, this paper provides an up-to-date comprehensive survey, classification, and critical analysis of the literature on corporate bankruptcy and financial distress predictions, including definitions of bankruptcy and financial distress, prediction methodologies and models, data pre-processing, feature selection, model implementation, performance criteria and their measures for assessing the performance of classifiers or prediction models, and methodologies for the performance evaluation of prediction models. Finally, a critical analysis of the surveyed literature is provided to inspire possible future research directions.

Introduction

Corporate bankruptcy prediction (BP) and financial distress prediction (FDP) have been a field of investigation by researchers around the world for nearly a half century. However, increasing attention has been paid to this evergreen subject since the Global Financial Crisis of 2008 (Alaminos et al., 2016), as predictions can have a significant impact on the decisions and returns of various stakeholders (Alam et al., 2021).

Corporate bankruptcy and financial distress events are not desirable (Gordon, 1971), as their legal and financial costs are prohibitive (Weiss, 1990). In addition, these events increase the expected costs for financial institutions, such as banks, to hedge against the risk of these events happening (Alnassar & Chin, 2015). To reduce exposure to risk and catch early warning signs, stakeholders including investors, bankers and governments are proactively looking for solutions to effectively analyze and predict corporate bankruptcy and financial distress events. The earliest study in terms of modern bankruptcy prediction can be traced back to 1932 when Fitzpatrick (1932) presented a successful way to distinguish between failed and healthy companies by analyzing 20 pairs of companies’ accounting ratios. Since the 1960s, several accounting-based statistical and probabilistic models have been proposed to predict corporate bankruptcy and financial distress (e.g., Beaver, 1966; Altman, 1968; Ohlson, 1980; Zmijewski, 1984; Zavgren, 1985). In addition, several studies focused on the identification of bankruptcy and financial distress drivers2 (e.g., Altman, 1968; Liang et al., 2016; Tobback et al., 2017; Tinoco et al., 2018; Mai et al., 2019), on one hand, and others focused on the design of methodologies for selecting such drivers (e.g., Tsai, 2009; Lin et al., 2014; Tian & Yu, 2017; Uthayakumar et al., 2020; Kou et al., 2021), on the other hand. Furthermore, a stream of literature investigated the causes of the under-performance of bankruptcy and financial distress prediction models such as data sample imbalance (e.g., Le et al., 2018; Veganzones & Séverin, 2018; Zoričák et al., 2020, Shen et al., 2020). In the era of the rise of machine learning and artificial intelligence technologies, the prediction of bankruptcy and financial distress has been lifted to a whole new level, as more and more new methodologies managed to improve prediction accuracy through the design features of new models (e.g., Ouenniche & Tone, 2017; Ouenniche et al., 2018a, 2018b, 2018c, 2019; Hosaka, 2019; Matin et al., 2019; Yuan et al., 2022), the type of implementation decisions such as over-sampling and under-sampling (e.g., Le et al., 2018; Sun et al., 2020; Shen et al., 2020; Du et al., 2020), and bagging and boosting (e.g., West et al., 2005; Zięba et al., 2016; Jones & Wang, 2019; Chen et al., 2020). On the other hand, another stream of research focused on reducing the computational requirements of prediction models or methods using parallel implementations that take advantage of today’s powerful computers, or to be more specific, GPUs (e.g., Huang & Yen, 2019; Le et al., 2019).

Conclusions and future research directions

The topic of corporate bankruptcy and financial distress prediction has attracted the attention of many researchers for several decades and continues to evolve with more and more advanced prediction methodologies and issue fixation solutions being proposed. This study contributes to this domain of research by providing an up-to-date state-of-the-art review, classification and critical analysis of the current BP and FDP literature, where six major research streams are identified and discussed, namely, the definition and coding of bankruptcy and financial distress; design of new prediction models/classifiers or new application of existing ones; design of new drivers or evaluation of existing ones; design or evaluation of feature selection methods; design of methodologies for the performance evaluation of prediction models; and issues affecting the performance of prediction models and related solutions. By painting the landscape of research and analyzing each research stream, this study would serve as a guide for researchers who intend to explore this field of study and/or contribute to its development.

Our analysis of the surveyed papers revealed a clear trend in terms of prediction methodologies of bankruptcy and financial distress, where more emphasis is put on advanced machine learning and artificial intelligence models such as ensemble learning models. Ensemble learning models and other methodological advances, such as DEA- and MCDA-based prediction methods, have contributed to further pushing the boundaries of research. Overall, it is fair to conclude that there is no single methodology that is better than the others, as each methodology has its strengths and weaknesses, some of which are design-related, and others are implementation decisions related, which have made the design and implementation of new ensemble models more popular.

Abstract

This literature review aims to examine the relationship between Green Human Resource Management (G-HRM) practices and various outcomes, including employee green attitudes, employee green satisfaction, client green satisfaction, employee green behavior, and organizational green performance. We reviewed existing literature on G-HRM practices and their impact on the selected outcomes. The review process involved the identification of articles through a systematic search in Scopus and Web of Science databases from January 2013 to December 2023. The search retrieved 2142 citations; of them, a total of 17 articles were deemed eligible for this review. The reviewed literature provides good evidence supporting a positive predictive relationship between G-HRM practices and employee green attitudes, employee green satisfaction, client green satisfaction, employee green behavior, and organizational green performance. However, there is a notable gap in studies exploring the influence of G-HRM practices on employee and client satisfaction. Overall, G-HRM practices emerge as a crucial tool for fostering environmentally conscious attitudes and behaviors among employees, ultimately contributing to enhanced employee satisfaction and improved organizational ecological performance. Future research should pay attention to the mechanisms underlying these relationships and explore potential moderating factors to enrich our understanding of the interrelated dynamics between G-HRM practices and sustainable outcomes.

Introduction

The growing concern for environmental sustainability and corporate social responsibility has prompted organizations to adopt alternative avenues to meet these responsibilities (Martin et al. 2014). As emphasized by the United Nations General 17 Sustainable Development Goals (SDGs), organizations need to operationalize and integrate sustainability in their strategy, plans, and actions. Therefore, they can address the current and forthcoming stakeholder needs and ensure a better and sustainable future for all, balancing economic, social, and environmental development (Fonseca et al. 2020). Moreover, academic research (Leal Filho et al. 2023) highlights the need for stronger action to avoid major challenges such as climate catastrophe. One way to foster sustainable practices can be the application of Green Human Resource Management (G-HRM) (Pham et al. 2020). G-HRM, as a general term, refers to the integration of environmentally friendly practices into HRM strategies and policies (Ren and Hussain 2022). It is increasingly recognized as a means to enhance an organization’s environmental performance and overall effectiveness (Munawar et al. 2022).

The adoption of G-HRM policies represents a proactive approach by agencies to enhance their environmental and overall performance. By integrating G-HRM practices into HRM strategies, organizations aim to foster positive attitudes, behaviors, and overall performance (Farrukh et al. 2022). Previous studies of the impact of G-HRM policies on employee and organizational performance in terms of green attitudes, satisfaction, behaviors, environmental performance, and client satisfaction provided promising results. The body of literature examining the impact of G-HRM practices on organizational and employee performance underscores the pivotal role that environmentally conscious human resource practices play in shaping both individual and organizational outcomes (Faisal 2023). Scholars such as Ren et al. (2018) assert that G-HRM practices significantly influence employee attitudes and behaviors toward environmental sustainability, fostering a sense of ecological responsibility among employees (Ren et al. 2018). Additionally, research by Albloush et al. (2022) suggests a significant relationship exists between G-HRM and organizational performance, as well as between G-HRM and human capital development, demonstrating that integrating sustainability into human resource strategies can enhance an organization’s environmental standing (Albloush et al. 2022). These findings align with insights from other works, such as those by (Baykal et al. 2023) and (Shafaei et al. 2020), which highlight the positive impact of G-HRM on employee job satisfaction and commitment to green initiatives. However, the literature also reveals nuanced outcomes, as observed in the research by (Aggarwal and Agarwala 2023), which identifies the mediating role of organizational culture in the effectiveness of G-HRM practices.

Conclusions

In conclusion, the reviewed literature provides good evidence supporting the positive predictive relationship between G-HRM practices and employee green attitudes, employee green satisfaction, client green satisfaction, employee green behavior, and organizational green performance. However, limited studies have examined the influence of G-HRM practices on employee and client satisfaction, and there is a need to include these outcomes in future studies. As organizations prioritize sustainability, G-HRM practices emerge as a critical tool for fostering environmentally conscious attitudes and behaviors, thereby contributing to both employee satisfaction and organizational ecological performance. Future research should focus more on the mechanisms underlying these relationships and explore potential moderating factors to further enhance our understanding of the dynamics between G-HRM practices and sustainable outcomes.

Abstract

The purpose of this research is to systematically review the state-of-the-art literature on Supply Chain Finance (SCF) and Environmental, Social, and Governance (ESG) and Value Chain within the supply chain management domain. We meticulously screened closely related themes through a systematic literature review of selected fifty-one manuscripts using the PRISMA method. Three-phase approach of planning, conducting and reporting is considered in this review. The outcomes of our review demonstrate the contributions of SCF to decision-making within the supply chain domain. This review highlights synergies, distinctions, and intersections in SCF, ESG, and value chain. Based on themes, the study led to four propositions to develop a comprehensive framework. Additionally, the literature is elucidated based on the approaches employed for SCF development, accompanied by the underlying theories. The categorization primarily separates the literature into two main groups: one focused on theory development, and the other on practical applications, revolving around SCF, ESG, and the value chain. Professionals in corporate settings and academic scholars will likely derive significant value from this review. The study thoroughly reviews, categorizes, and analyzes existing research and offers an integrated framework on SCF, ESG, and the value chain, which can be helpful for professionals. This is the first research that uses a structured approach to analyze studies on a novel topic and propose a framework for SCF, ESG, and value chain.

Introduction

In the last twenty years, a notable pattern has surfaced in the realm of corporate sustainability. This trend encompasses a range of initiatives, from mandates that encourage voluntary commitments to sustainable practices (Freeman et al., 2010; Wang et al., 2016; Aragòn-Correa et al., 2020; Fiandrino et al., 2022; Agrawal et al., 2023). Thus, along with sustainability strategies companies have also started sharing information about environmental, social, and governance (ESG) matters (Baid and Jayaraman, 2022; Asif et al., 2023; Kumar et al., 2024). Sustainability and ESG have attracted significant importance in the business landscape. Business need to incorporate these revolutionary changes to comply to emerging business environment. ESG captured the interest of various stakeholders such as scholars, governments, and enterprises through a report published by United Nations in 2006 (Atkins, 2020; Clément et al., 2023; Wang et al., 2023a,b). In 2021, ESG-focused portfolios accomplished nearly $40 trillion in assets further expecting a 30% increase by 2025 (Bloomberg Intelligence, 2021). This brought transparency in all the activities that could impact the environment. Exposure by social media and non-government firms led to an increase in global SC visibility (Clarke and Boersma, 2017; PRI, 2020; Saini et al., 2022; Fiandrino et al., 2022; Agrawal and Jain, 2022; Agrawal et al., 2024).

The global financial crisis of 2008–2009 witnessed increase in research on Supply Chain Finance (SCF) (Kaur et al., 2023). This crisis revealed that companies and their SC faced cash flow constraints and challenges in securing financing from banks. These difficulties were often attributed to a lack of understanding of liquidity and working capital management (Caniato et al., 2016; Baid and Jayaraman, 2022; Huang et al., 2022; Rijanto, 2024). Since then, SCF has progressively evolved as a crucial tool for tackling these challenges. The primary focus of SCF revolves around “planning, managing, and controlling SC cash flows,” as Wuttke et al. (2013) emphasized. According to Jia et al. (2020), aims to help companies fulfill their daily financing needs, optimising cash flow at the inter-organizational level. The concept of SCF is a recent development as compared to equity financing or mortgages and it faces numerous challenges, as emphasized (More and Basu, 2013; Joshi et al., 2024). It is evident that number of start-ups are also emerging in SCF space to facilitate businesses in their transactions. Emerging approaches in SCF include purchase order financing (Reindorp et al., 2018) and inventory financing (Yan and Sun, 2013). As SCF garners increasing attention, the volume of literature in this area is also rising (Gomm, 2010; Elliot et al., 2020; Jia et al., 2020; Medina et al., 2023). However, investigation on SCF or the convergence of finance and operations is yet in its early stages, primarily because of its innovative nature. As per the PRI (2020), adeptly managing ESG factors in SCF can yield a range of short-term and long-term financial benefits.

Conclusion

This review assesses 51 papers from 1999 to 2023 from the Scopus database. Fig. 4 illustrates the evolution of ESG, SCF and VC research over time, showing a significant upswing in activity from 2018 onwards. Fig. 2 reveals that in ESG, SCF, and VC, research predominantly occurs within decision sciences, engineering, computer science, business management, and accounting. Additionally, the analysis explores the facilitators and gaps associated with ESG, SCF and VC, as outlined in Section 2.3. The rising interest and application of ESG, SCF and VC, focused on tasks like economic values and minimizing its environmental impact, all the stakeholders are ethical and transparent, optimize the cash flow, improve efficiency and financial stability for offering practical solutions to contemporary business challenges. The exhaustive nature of this inquiry aims to provide a valuable and practical resource to all the stakeholders, particularly for future researchers in the field of production research. This investigative framework developed here can be a foundation for forthcoming research endeavors.

Abstract

Objective
To examine the prevalence and trend of experimental research on the effectiveness of ICT use in supporting the management of mass casualty incidents.

Methods
A systematic review was conducted in five electronic databases between February and March 2022 following the PRISMA guidelines. The analysis included studies published since 2012.

Results
A total of fifteen studies were included in the final analysis. Three themes were identified: 1) the response of medical teams to mass casualty incidents, 2) the simulation of mass casualty incidents, and 3) the digitisation of mass casualty incident workflows.

Conclusion
The available evidence is limited due to the relatively small number of studies on the use of information and communication technology and the response of emergency rescue teams to mass casualty incidents. Therefore, further research is needed on the impact of information and communication technology on the efficiency, work, and decision-making of incident commanders during mass casualty incidents. Furthermore, more dynamism is needed to accumulate knowledge and methodological expertise to explore experimental ideas in the European Union, where such research is lacking.

Introduction

To ensure that Emergency Medical Teams (EMTs) are always prepared for Mass Casualty Incidents (MCIs), it is crucial to anticipate and plan for such situations, even though they may be rare. Although there have been several attempts to define an MCI quantitively, the best definition is that the number of casualties exceeds the resources generally available at the scene [1]. In this article, we refer to MCIs not caused by terrorist attacks. The rationale for excluding them is rooted in the significant differences in managing such MCIs, which stem from the deliberate intention behind these events and the often disproportionate number of casualties they cause [[2], [3], [4], [5], [6], [7], [8]]. Between 1982 and 2012, 290 mass casualty incidents (MCIs) were analysed in the study conducted by Turris, Lund, and Bowles [9]. Out of these MCIs, 71 (24 %) occurred in Asia, 69 (24 %) in Europe, 48 (17 %) in Africa, 48 (27 %) in North America, 27 (9 %) in South America, 25 (9 %) in the Middle East, and 2 (1 %) in Australasia. In Slovenia, an MCI occurs on average once a year [10].

Efficient and rapid deployment of rescue services is critical. In such circumstances, the approach and execution of rescue service operations are very specific. Through the proper use of available resources, every effort must be made to save the lives and health of as many people as possible. Such an event regularly exceeds the depleted capacities of local services and the nearest hospitals. It requires rapid reorganisation of work and support from additional rescue teams and other hospitals. The main goal of the disaster response organisation is to fulfil the necessary tasks and reduce the number of fatalities in the first hours after a disaster. To manage MCIs safely and effectively, EMTs need the appropriate knowledge and skills. The prehospital phase of an MCI is typically chaotic, dynamic and evolving in nature, requiring prehospital management decisions to be made under extreme time pressure. In an MCI, evacuating severely injured patients to an appropriate medical facility is critical.

Conclusions

ICT has the potential to improve crisis management, particularly in the context of EMTs actions during MCI. Further research is needed to determine if digital transformation optimises medical teamwork through advanced ICT, leading to more effective management decisions and increased chances of survival in MCIs. This study provides evidence for future researchers to conduct experimental research, especially within Europe.

In summary, these studies collectively unveil the multifaceted applications of ICT in mitigating the complex challenges inherent in MCI. From innovative triage protocols and aerial surveillance using drones to telehealth systems, advanced training methodologies such as AR/VR, AI, and machine learning for data analysis, and ethical considerations surrounding high-fidelity simulations and game-based training, these findings contribute to a comprehensive understanding of how ICT can augment preparedness, response, and training for MCI. As the academic community continues to delve into this domain, the integration of ICT remains pivotal in reshaping disaster response emergency response and management paradigms, ultimately bolstering societal resilience in the face of unforeseen calamities.

Abstract

With this study, brand managers can have an overview of the major concepts and characteristics of brands over time, while academics receive a mapping of the most analyzed topics and suggestions for future research. Based on the documents published in Scopus and Web of Science databases using the word “brand”, this article aims to provide an overview of the brands and suggest opportunities for future research. Text mining clustering allowed the processing of a large amount of information and organized the first overview of the concepts that have been studied. Thus, first, we examine the existing definitions of a brand. Then, we provide a historical perspective of the topics associated with brand constructs and their associations and present a framework for the psychological characteristics of the branding process. Finally, we present the future trends.

Introduction

Originally the term “Brand” referred to a piece of burning wood. In the Middle Ages, it becomes a verb meaning a permanent mark with a hot iron. In the seventeenth century, it represented a mark of ownership (Ries & Ries, 2005). Yet, it is in the late nineteenth and twentieth centuries that it grows in relevance and started to designate goods, services, and institutions, but now also destinations, people, and robots. Brands are present in human lives in the physical, online, or virtual world (Loureiro et al., 2021).

Brands and studies on brands have rapidly evolved over time and there is a need to map such evolutions to guide both researchers and practitioners. Other reviews discuss some particular aspects of branding by focusing on specific concepts—for instance, authenticity (Nunes et al., 2021), engagement (Bilro & Loureiro, 2020), love (Gumparthi & Patra, 2020), or human brand (Osorio et al., 2020)—or are devoted to a certain context (e.g., Bhattacharya & Sen, 2003; Hollebeek et al., 2014), period of time (Górska-Warsewicz & Kulykovets, 2020; Barros-Arrieta & García-Cali, 2021; García-Cali), or are dedicated to the global versus local symbolism of the brand (Liu et al., 2021), lacking a more holistic perspective of brands. Because brands and their concepts are a core topic in marketing, it is relevant to aggregate the knowledge to offer a summary view on the topic.

Concluding thoughts

This overview of the extant literature identifies important steps in the progress of the research on brand. Thus, earlier studies started to be more dedicated to brand choice, quality assurance, brand equity, perceived risk, or corporate reputation. In the late 1990’s the concerns about the relationship between brand and consumers become more relevant. In the twenty-first century, the studies on the psychological consumer perception of brands become gradually more frequent, such as: brand personality, brand experience and brand love. In those days, social media and e-commerce shifted the focus on physical goods/services to online ones. Brand engagement and co-creation both online and offline are key words for academics and brand managers. More recently, brand authenticity and brand coolness are relevant to better understand the preference of consumers. As brands are conquering virtual and artificial contexts, the studies on this topic gain popularity.

The academic audience can benefit from this research by having a summary of the literature and suggestions for future research. Hence, this article offers a timeline on the evolution of the content of publications, where it is possible to observe the most analyzed concepts in each decade. Thus, this article provides readers with an overview of how concepts, meanings and trends in branding have evolved over time. Secondly, academics can use the framework for the psychological characteristics of the branding process in their research, where it is possible to understand the associations between core branding concepts. Thirdly, Table 2 can be a guide for potential further research on the topic.

Abstract

We review dynamic quality models both in single-agent setup and in a competitive framework. Our objectives are: (1) to give the reader a vantage point on the state of the art in this area, (2) to identify the boundaries between the different concepts of quality to help build a bridge between the various communities interested in the management of quality, and (3) to sketch out a research agenda for the area. The paper should not only be of interest to active researchers in the field, but also to a broader community of scholars and practitioners working in operations management, marketing, industrial engineering and operations research, who are interested in quality dynamics.

Introduction

During the three last decades or so, a large literature has developed on product quality management, with one stream using a dynamic model to reflect the idea that firms can improve the quality of their products over time. This paper surveys this dynamic literature both in a one-firm framework and in a competitive setup. There are several reasons for adopting a dynamic model when dealing with product’s quality. First, consumers’ tastes change over time and if the firm wants to remain competitive (not to say survive) in the market, it must upgrade continuously the quality of its products. Second, changing product’s quality requires constant investments over time to, e.g., improve production processes and use better materials. Third, environmental and safety regulations change over time and so must the product’s quality about may impose some. Finally, establishing a high-quality reputation needs sustained marketing as well as operations efforts.

We all have probably witnessed two friends discussing a product quality or brand’s quality and ending in a deadlock. One likely reason for this outcome is that each party had her own personal definition of quality. Such differences in opinion also occasionally involve consumers and firms. For instance, a new product can be a true marvel from an engineering and production point of view, but be snubbed by consumers because it does not suit their tastes, and therefore be labeled a poor-quality product. Then, one can ask the following simple question: can quality be assessed through a reliable and valid measurement scale? In a seminal paper, Garvin (1988) suggested the following eight dimensions to measure this construct:

Conclusion
This paper surveyed the contributions on quality dynamics both in single-agent and in competitive situations. In this section, we propose some ideas for future investigations, with some of them being relatively straightforward extensions to what has been done, and others being more conceptual (and sometime speculative) ones.

Stochastic models: Looking at the “Model” column in the Appendix, we clearly see that the literature has largely adopted a deterministic model. Given that one can hardly argue that e.g., future demands and costs are known with certainty, the choice of a deterministic setup is, at least partially, motivated by mathematical tractability. Still, this choice has allowed researchers to obtain a series of insights into the management of quality over time. Extending most of the proposed deterministic models to a stochastic environment is conceptually easy, but it will come with the cost of losing the opportunity of having closed-form solutions. Also, depending on how uncertainty is introduced, obtaining a numerical solution may be computationally challenging, especially for multi-agent models with strategic interactions. One good place to start the analysis is to consider a two-stage model where quality decision is made once, while other decisions, e.g., pricing and advertising, are made in both periods. This would allow one to gain intuition on how uncertainties in, e.g., demand or cost, affect the quality decision in current and future periods. Next, one can move to a multistage model where quality decision is made in each period.

Abstract

Using a proprietary dataset from an Australian leading FinTech lender, we provide insights into the effect of consumer behaviour on FinTech lending patterns. Out of seven consumption categories, gambling expenses significantly reduce the lender’s willingness to fulfill loan requests. Cash usage and repeated borrowing are related to lower offer-to-requested loan ratios. The FinTech lender prefers to lend to borrowers who are married, have dependents and/or aged over 30. However, for such mature borrowers, cash usage and repeated borrowing increasingly reduce the approval likelihood of their loan requests. Taken together, our empirical evidence suggests that consumer behaviour affects FinTech lending decisions.

Introduction

In this study, we provide new evidence on the relationship between consumer behaviour and credit access using a novel data by a leading Australian FinTech lender specialized in short-term consumer credit products. FinTech firms have garnered increasing attention amongst policy makers and regulators given its disruption to how traditional businesses are conducted in the consumer credit market, particularly through open banking initiatives. Jagtiani and Lemieux (2019) show that FinTech lenders utilize more soft information from alternative data sources in screening and this business process benefits borrowers who would otherwise be unable to obtain credit. Di Maggio and Yao (2021) investigate FinTech lenders’ pricing strategies and borrower outcomes using a large dataset on household balance sheets. They find that FinTech lenders rely on hard information from credit reports rather than soft information or alternative data.

We contribute to this growing literature by presenting novel evidence on how soft information from bank statements surrounding payment and consumption behaviours affects the willingness of FinTech lenders to fulfill loan requests. Prior studies have shown some alternative data, such as applicant’s appearance, social network and writing style, etc., used in FinTech lending (e.g., Herzenstein et al., 2011; Lin et al., 2013; Gonzalez and Loureiro, 2014; Dorfleitner et al., 2016; Freedman and Jin, 2017; Buchak et al., 2018; Jiang et al., 2018; Croux et al., 2020). Our unique dataset allows us to show that FinTech lender’s willingness to supply credit depends on the consumer behaviour revealed from information contained in bank statements and applicant demographics. Moreover, to the best of our knowledge, we are amongst the first to study the effect of consumer behaviour on FinTech lending, while most extant studies focus on the implications of FinTech lending on borrowers (e.g., Gathergood et al., 2019; Di Maggio and Yao, 2021) or the prediction of defaults (e.g., Khandani et al., 2010).

Conclusion

This study examines the relationship between consumer behaviour and credit access using a novel data by a leading Australian FinTech lender specialized in short-term consumer credit products. Our findings provide an Australian perspective to the growing literature on FinTech lending which uses primarily U.S. data. Our unique dataset reveals that FinTech lender’s lending decisions depend on loan applicants’ consumer behaviour. To the best of our knowledge, we are amongst the first to study the effect of consumer behaviour on FinTech lending, while most studies focus on the implications of FinTech lending on borrowers (e.g., Gathergood et al., 2019; Di Maggio and Yao, 2021) or the prediction of defaults (e.g., Khandani et al., 2010).

This study has its limitation. Due to the data constraint, we can only show the association, but not causal relation, between loan applicant’s consumer behaviour and FinTech lending. Nevertheless, we believe that the findings on the association between consumer behaviour and FinTech lending may still be of interests to FinTech borrowers, academics, and/or regulators. For example, our findings suggest that in the FinTech era, loan applicants need to be aware that their cash usage and gambling expenses can affect their borrowing capacity.

Abstract

The circular economy (CE) has emerged as a sustainable alternative to the linear model of production and consumption of products and services. Consumers are key actors in the circular economy loop, yet consumer behaviour and decision-making remain at the periphery of research in this area. To close this gap and to promote related academic research we perform a systematic literature review, analysing the main areas of research in the CE relating to consumer behaviour and decision-making. The results show that there are six main areas that link consumer and CE: consumer behaviour, purchase intention and sustainable consumption; lifetime and reparability; recycled plastics, upcycling, e-waste and innovation. These areas seem incomplete and focused on a relatively small number of sectors. Further, while attitude and knowledge are the most influential elements in the consumer’s buying decision-making process, our analysis shows significant gaps in current research in this regard. A key element of consumer behaviour, the post-purchase phase relating to “use”, “recycle” and “upcycle” was found to still be obscure. We provide recommendations on how this gap can be filled.

Introduction

The circular economy (CE) has been gaining increasing attention in recent years from society, companies and public bodies (Korhonen et al., 2017). The best-known economic model until now was the linear model, based on continuous growth and the use of many resources (Kirchherr et al., 2017; Ness, 2008). The CE has emerged as an alternative to this model, due to the fundamental positive role it plays in the environment, its functions and its interactions with the economic system (Ghisellini et al., 2016). The concept of CE has been reformulated and analysed several times in recent years (Geissdoerfer et al., 2017; Ghisellini et al., 2016; Kirchherr et al., 2017; MacArthur et al., 2013; Prieto-Sandoval et al., 2018), with researchers agreeing that it is a regenerative production and consumption model. However, it cannot be regarded as an individual process, as the CE involves a change in companies, industries and the economy through shifts in values, norms, behaviours and attitudes in society (Chizaryfard et al., 2021).

To this effect, the concept of CE is being analysed from different fields such as economics, strategy, engineering and resource consumption (Clube and Tennant, 2020; Demirel and Danisman, 2019; Machado et al., 2019; Perez-Castillo and Vera-Martinez, 2021), although there are still few studies concerned with the impact of consumers on the CE loop. Consumers must be involved in the whole process and be aware of the value of CE-based products and services. However, as stated by (Kirchherr et al., 2017), the reasons why consumers do or do not take part in CE processes have not been sufficiently analysed (Camacho-Otero et al., 2018). established that although there is increasing research on consumption, the contributions often refer to possible solutions relating to the nature or meaning of CE or the consumption progress, but do not focus on the relationship between the CE and the consumer. In turn (Wastling et al., 2018), argued that the role of the consumer in the CE needs to be questioned and has not yet been fully explored. To this end, there is a need to analyse the role of consumers to resolve the existing gaps in the current literature. However, not only is the relationship between CE and consumer essential to understand, but so are the behaviours and attitudes that consumer may have regarding this process, considered a hot topic due to the wealth of information it brings to both companies and society (Stankevich, 2017). The consumer can be analysed effectively through the decision-making process, wherein the consumer is at the centre (Zhang and Benyoucef, 2016).

Discussion and conclusions

Based on this literature review, it was found that interest in the relationship between the CE and the consumer has increased in the last two and a half years, when 75% of the documents analysed were published. This reflects the fact that it is a new topic that has a long way to go, and one that is important not only at European but also at global level. This literature review provided an overview of and revealed the deep research in the existing literature regarding the CE and the consumer, in terms of consumer behaviour and consumers’ PI.

To answer the first research question – What are the main areas of research in the CE relating to consumer behaviour? – this paper summarises and interrelates the different main areas of the CE with the consumer. Notably, seven different main areas were detected, all of them interrelated, as shown in Fig. 7. A circular economic model is presented, composed of “take, make, distribute, purchase, use and dispose”, adding “recycle, upcycle and innovate”. The CE was the main concept analysed, from which six different main areas were obtained that can be connected to the circular chain in terms of consumer behaviour. They were (1) the elements that affect consumers’ behaviour, PI and sustainable consumption; (2) lifetime extension and reparability; (3) packaging and recycled plastic; (4) e-waste; and (5) upcycling. Moreover, it was identified that process improvement and involvement depend on (6) innovation, as a way to reduce barriers to CE adoption and to contribute to a more sustainable economy, and so is considered a key factor within the CE loop. Each of the areas mentioned, except for the “purchase” area, which deals with the key concepts of consumer behaviour and attitudes, analyse consumers in a superficial manner, focusing more on the product or service than on consumer reactions or behaviours. To this effect, an important gap is detected in the literature, and that is the lack of knowledge of consumers in actions such as decisions to extend the life of a product, how consumers perceive the changes in new consumption models, and even how they can be re-educated in relation to concepts based on the CE.

Abstract

Stakeholder-based brand is increasingly recognized as a measure for corporate sustainability, although the knowledge in this area is relatively unknown. Through a systematic review approach, the present study explores the global knowledge base on sustainability and brand. The most influential authors and documents are identified, followed by a discovery of the intellectual structure of the sustainability and brand knowledge base with five schools of thought. First, the Customer Attitudes and Behavior school refers to behavioral studies (one of the common approaches in sustainability studies). Second, the Tourism Marketing school represents the popular context of sustainability studies that mainly relates to hospitality, destination marketing, and fashion brand management. Third, the Brand Strategy school refers to corporate strategy concerning brand that is widely used to measure corporate sustainability performance such as brand equity. Fourth, the Societal Marketing school provides insights into the marketing strategy that leads a firm to achieve competitive advantages under concerns about finite resources and rising environmental and social costs. Finally, the Advanced Quantitative Analysis school reveals an approach that is mainly used when conducting sustainable marketing studies. A model on sustainability brand is then derived, adopting the grounded theory approach. Future research opportunities are also identified and discussed to continuously advance the scholarship in this specific area.

Introduction

Competitiveness through tangible practical benefits is no longer viable in today’s cut-throat business environment. For this reason, a company’s brand—which is viewed as providing both practical and intangible benefits—is essential to its long-term viability. Corporate brand is being valued more and more due to the increasing interest about business sustainability. Given the impact it has on the attitudes and behaviors of consumers, the corporate brand eventually affects the financial performance of the company. It stands for business strength and reputation in the marketplace [1,2]. The collective value of a brand or brand equity is a crucial component that describes a company’s performance as perceived by its stakeholders [3]. It responds to the idea that a company’s stakeholders should look at how well the company performs in terms of sustainability and how well its stakeholder-focused strategies and practices work [4]. According to research that was carried out in the past [5,6], one of the most critical factors that determines a company’s reputation is how its social performance is seen by the public or stakeholders. This increases brand equity. According to Avery and Bergsteiner [7], corporate sustainability should be achieved by building a strong brand and reputation. Similar to this, several studies have discovered that CSR results in brand equity and business reputation and that a positive reputation can result in long-term profitability and consistently higher performance [8]. In addition, a corporation can benefit from cause-related activities [9] by enhancing the position of the brand, increasing favorability for the brand, raising the volume of the revenues, boosting loyalty among customers, and creating strong bonds with alliances and social organizations.

Brand equity, according to Aaker [10], increases the firm’s worth through boosting marketing campaigns’ efficiency and effectiveness, as well as customer loyalty, prices and profit margins, brand expansion, trade leverage, and competitiveness. Whilst others have claimed that brand equity is determined by the added value that the brand name brings to a product (e.g., [7]), Aaker [10] defines brand equity as a collection of brand assets and liabilities associated with the brand’s name and symbol. The value provided by a service or product may be reduced or increased as a result of this grouping. Undoubtedly, a company’s perceived reputation should reflect both its past and future actions and, in comparison to its rivals, should reflect the firm’s total appeal to all significant stakeholders [11]. Additionally, some scholars [12,13] have claimed that brand equity is determined by the overall value that a brand offers to one of its primary goods. The brand equity model includes associations with the brand, a user’s impression of the product’s quality, and other proprietary aspects of the brand in addition to brand loyalty, brand name awareness, and perceived brand quality [14]. Building a powerful brand involves considering all of these aspects as part of the process [15,16,17].

Conclusions

Through the systematic review approach, the present review has provided the answers to the five research questions. First, we identify the most influential authors and documents regarding sustainability brand. The top four influential scholars in the specific sustainability brand knowledge base are: Gupta, Suraksha; Gupta, Shuchi; Kumar; Kantabutra. Accordingly, their eight documents are the most influential documents in this specific knowledge domain. Second, we discover the topical foci and most popular topics that scholars in the sustainability and brand literature are interested in. Some of the most recent topics are brand, brand loyalty, brand image, brand equity, and buying intention.

Third, we reveal the intellectual structure of the sustainability and brand knowledge base by identifying five schools of thought in the knowledge domain. First, the Customer Attitudes and Behavior school refers to behavioral studies (one of the common approaches in sustainability studies). Second, the Tourism Marketing School represents the popular context of sustainability marketing studies that mainly relate to hospitality, destination marketing, and fashion brand management. Third, as in the Brand Strategy school, the brand strategy such as brand equity is widely used to measure corporate sustainability performance. Fourth, the Societal Marketing school provides more insights into the marketing strategy that leads the firm to achieve competitive advantages under the concern about finite resources and rising environmental and social costs. Finally, the Advanced Quantitative Analysis school reveals an approach that is mainly used when conducting sustainable marketing studies.

Abstract

Disasters – natural or manmade – are on the rise with far-reaching implications for international business (IB) actors and transactions. While the Covid-19 pandemic has generated much academic interest for its impact on business in general, little effort has been made to consolidate the fragmented research on disasters more broadly in the field of international business. Therefore, it is important and urgent to consolidate the existing knowledge to provide a solid basis for future research. We systematically review 132 articles published between 1991 and 2022 and critically evaluate the nascent but rapidly growing literature at the intersection of disasters and IB. Our examination of the different types of disasters (natural and manmade) shows two separate streams: (1) a dominant MNE-centric stream of strategic IB research which regards disaster as an exogenous shock impacting MNE strategies, responses, and resilience, and (2) an emergent stream which places disaster as a more central, embedded phenomenon of investigation impacted by MNEs and other global actors. Our systematic review highlights the gaps in this literature and concludes with a discussion of the intersection of IB-disasters in relation to the 17 United Nations’ Sustainable Development Goals (SDGs) to suggest directions for future research.

Introduction

Disaster impact and frequency have tripled over the last fifty years (Al Adem et al., 2018; Thomas & López, 2015) with devasting effects on people and environments worldwide. The Covid-19 pandemic has become one of the most severe exogenous shocks to political, economic, and social stability in modern history (Alonso et al., 2021; Baker & Judge, 2020). Other recent devastating natural disasters, including floodings, hurricanes, wildfires, and draughts, many of which are climate-related, have caused a diaspora of people, illness, and death throughout the world. As of this writing, the ongoing war in Ukraine as well as other recent manmade disasters, including sabotage, terrorism, and industrial disasters, continue to cause widespread destruction and distress wherever they occur.

Both manmade and natural disasters have a significant impact on International Business (IB). For instance, the 9/11 terrorist attacks on America caused significant economic damage in the immediate aftermath, rippling through global financial markets (e.g., Czinkota et al., 2010). Airlines and insurance companies took the hardest immediate hit, and U.S. stock markets initially fell more than 10% in the days after (Davis, 2022). The World Investment Report 2021 shows that the Covid-19 pandemic has reduced global Foreign Direct Investment (FDI) in 2020 by 35%. After Hurricane Katrina in 2005, oil production and refining were shut down for weeks affecting global oil prices (e.g., Byard et al., 2007). The volcanic eruptions in Iceland in 2010 grounded flights in Europe and beyond for weeks resulting in major disruptions to supply chains as well as business and tourist travels. Wildfires, flooding, and manmade disasters such as wars continue to wreak havoc on IB transactions, with the Ukraine crisis a stark reminder. These examples provide strong evidence of the massive effects of disasters on both national and global economies, and IB more generally.

Conclusion

Our review article took stock of the state-of-the-art of IB-disasters research and provided examples and guidance for future IB scholars in this embryonic cross-field. Our categorization into manmade versus natural disasters illustrated the differential impact of a variety of disasters on IB actors. We concluded that most existing research in this field is treating disasters as exogenous shocks and focus primarily on disaster management from an MNE-centric perspective. Yet a more inclusive view of disaster embeddedness expands the definition of IB to encompass a broader scope and set of actors that engage in cross-border multidisciplinary activities to address grand challenges, such as the 17 SDGs. Hence, to conclude we call for IB researchers to focus on how disasters – natural and manmade – are driving (or exacerbating) many of the grand challenges facing society, and what critical role(s) IB actors can play as intermediaries to help accomplish SDGs. We believe that the intersection of IB and disasters opens many exciting new avenues for research that have hitherto been neglected. Such a research agenda will likely push the boundaries of the firm and its place in local and international communities and facilitate cross-disciplinary research to help build a better world.

Abstract

The Internet of Things (IoT) is becoming pervasive and with each new installation of IoT platforms new and legacy brokers have to be exploited. New internal brokers are those under the control of the platform, while legacy external brokers are those in place managed by third parties. The solution proposed addressed problems of (a) interoperability to reduce set up time to cope with unknown data structures (devices, entities) distributed via brokers; (b) performance by dimensioning both front-end and back-end processes to reach high rates in a broker-based platform, while preserving full capability features of the data warehouse. Interoperability aspects have been addressed by introducing our concepts and a reasoner into an IoT Directory tool to manage Internal and External brokers, automate device discovery and registration from both standard and customized data models. Despite the managed complexity, a broker-based solution turned out to provide high performance. To this end, a specific assessment and architecture tuning have been performed and reported in the paper to give evidence and validation. The proposed integrated IoT Directory has been developed in the context of the Herit-Data Project, and it is currently used in the whole Snap4City network of 18 tenants and billions of data. Snap4City is an open-source IoT platform for Smart Cities and Industry 4.0, which is an official FIWARE platform and solution, EOSC service and libs of Node-RED.

Introduction

The Internet of Things (IoT) defined a paradigm for the computation and communication amongst things, which is becoming every day more and more pervasive and adopted in many different domains [1,2]. It is partially due to the worldwide intense deployment campaign about Low-Power Wide Area Network technologies [3], as well as to many approaches and protocols for communications amongst devices (e.g., Message Queue Telemetry Transport or MQTT, Next Generation Service Interfaces or NGSI, Advanced Message Queuing Protocol or AMQP, Constrained Application Protocol or COAP). The approach is also covering the cloud and fog infrastructures [4,5]. Thus, IoT network infrastructures are becoming every day more complex to be managed due to the networks’ structure and existence of several protocols, formats, and concepts [1,6]. Hence, the complexity is growing in terms of data management, not only for huge amount of data but also for interoperability and abstraction levels needed to data managing. Relevant aspects to be considered are security and privacy [7] on specific data models and entities. To increase the complexity, there is a range of different owners and managers who may control different parts of such IoT networks [8].

In this context, the concept of Gateway is relevant for any segments of IoT networks connecting, as well as for the Web of Things, WoT [9]. Gateways may be integrated with one or more Brokers to send/receive data to/from Devices/entities. The Gateways and Brokers are typically compliant with a single protocol and may be managed by third parties with respect to data management platform. In some cases, they are provided as public services for several interested customers in the same area (for example: Proximus for LoraWAN services [10]). A Gateway may abstract from the IoT Broker level managing multiple brokers for multiple organizations/tenants (which can be regarded as customers of Gateway services to manage several Devices), via some API and/or Web user interface. Typical IoT Brokers can only manage one organization, and thus are single tenant, meaning they broker messages using topic/entity concepts (which can be regarded as the key for subscription on that specific device/entity) without any internal partition of services, but as a sort of family of devices and subscriptions. Some IoT Brokers can be multi-tenant, such as the FIWARE Orion Broker [11,12], which provides support for partitioning the served devices/entities/topics in groups, and each of them may have a dedicated service/path for a specific scope (or a specific customer). Furthermore, devices of different tenants could exist physically in different places (even having identical identifiers, IDs), and the subscription to the broker’s tenant may imply receiving all messages/services in the partition in push. That is feasible only if the subscriber knows the service/path identifier and, in the event of access control, the subscriber has the grant to access the broker’s services. Different IoT Devices connected to the same broker adopt the same protocol, may use different data structures/models and have the same semantic information.

Conclusions

The proliferation of IoT devices, brokers, networks, data models, operators and tenants, makes the harmonization and management of IoT Platform a hard goal. This paper offers an analysis and a comparison amongst relevant existing platforms, and it points out the basic requirements to achieve such aims. These identified requirements are in most cases not addressed by main platforms which prefer to stay on their own end-to-end solutions with limited interoperability and capacity of exploiting legacy IoT networks in place, in terms of performance. The proposed solution addressed problems of (a) interoperability by reducing set up time to efficiently detect and learn how to process unknown data structures (devices, entities) distributed via brokers; (b) performance by dimensioning the front-end and back-end processes to reach high rates in a broker-based platform, while preserving full capabilities features of data warehouse.

As to interoperability, the main identified and solved problems are those related to a large variety of Data Models coming from non-controllable External Brokers. The issue has been solved by designing and implementing a harvester and reasoner that is capable to automatically recognize/understand and map the new data models/types into those already known by Knowledge Base. This approach, together with the definition of a comprehensive meta model and dictionary, has allowed to speed up the process more than 800 times. The harvesting and comprehension process can be periodically performed to keep the platform updated with any newly defined data models by third party brokers. Furthermore, the process is helped by Km4City ontology and Data Dictionary to recognize the new data types and models according to the semantic domain.

Abstract

Introduction

     Innovation and international business are essential to achieve competitive advantages in currently unforeseen business environments. Today’s company seeks innovation in its country of origin and abroad in order to compete globally. Thus, incorporating this concept into international companies’ strategies is a main issue nowadays.

Purpose

     The aim of this systematic study is to improve the current knowledge on the relationship between innovation and international business, as well as identifying innovation tendencies for corporations to acknowledge the opportunities and challenges of this area’s development in the international business context.

Methodology

     Despite the abundance of innovation and international business reviews, joint reviews of both of them cannot be found. This study is the first to combine the scholarly research on both topics with the systematic literature review of academic literature of 28 years, following the PRISMA guidelines and flowchart. A search was carried out in Web of Science database; 847 initial documents were obtained and, after reviewing multiple documents according to the inclusion/exclusion criteria, the results for this research work were reduced to 236 articles.

Results

     The results of this research provide an overview of the knowledge structure of innovation and international business. As the main contribution, the results highlight four themes of investigation within a comprehensive and multidimensional framework: Innovative activities of multinational corporations, Global value chains, Innovation in emerging economies, and Cross-border knowledge. With an international perspective, insights from how to face innovation development in the international business context are presented.

Conclusions

There is a strong relationship between innovation and international business. These four research trends highlight the strategic importance of innovation in the international business field. Finally, the most interesting paths for future research are identified, targeting opportunities for improvement in both areas. This systematic literature review is expected to make significant contributions to both theory and practice in the field of innovation and international business.

Introduction

     Innovation, knowledge and technology are relevant concepts in the international business field [[1]] and both areas are essential to achieve competitive advantages in current business environments [[2]]. Cantwell [[3]] adds that innovation and internationalization processes have been increasingly interlinked as key drivers of development since the first industrial revolution, all the way to today’s information age.

     Innovation is the cornerstone of growth and sustains organizations to counter marketplace fluctuations and prepares them for long-term growth [[4]]. Business model innovation, although it is very difficult to achieve [[5]], can itself be a pathway to competitive advantage if the model is sufficiently differentiated and hard to replicate for incumbents and new entrants alike [[6]]. New models of innovation have encouraged many innovative firms to change the way they search for new ideas, adopting open search strategies that involve the use of a wide range of external actors and sources to help them achieve innovation [[7]].

     The field of international business studies came to prominence in the 1980s and early 1990s with the growth of multinational corporations [[8]]. In this framework, two theoretical models are extremely relevant; on the one hand, gradual internationalization or Uppsala model, according to which internationalization is seen as an incremental process that begins in foreign markets, being in closer proximity to the domestic market in terms of physical distance [[9],[10]] and, on the other hand, born global firms, that is to say, companies that internationalise at or near their founding, on an average period of three years of founding, generating at least twenty five percent of their total sales from foreign countries [[11]]. There is an extensive literature about this issue [12, 13, 14].

Conclusions 

     Nowadays, companies seek innovation in their countries of origin and abroad in order to compete globally. Therefore, innovation is a key factor for entering into international markets. This systematic literature review shows that there is indeed a strong relationship between innovation and international business; four themes of investigation within a comprehensive and multidimensional framework are found: Innovative activities of multinational corporations, Global value chains, Innovation in emerging economies, and Cross-border knowledge. These four research trends highlight the strategic importance of innovation in international business. Nevertheless, even when the number of articles addressing such topics is growing, this research work underlines that there is still a great opportunity for studying the relationship between those concepts. Thus, incorporating innovation into internationalized companies’ strategies is a main issue in current times, even more considering the changing and challenging world that we live in.

Abstract

     Despite the growing attention which green human resource management (GHRM) has been gaining, the field is still remarkably young, and conceptual clarity is yet to be attained. A bibliometric review of GHRM from 2010 to 2020 was conducted on the Web of Science and analyzed using the VOSviewer software package, version 1.6.16 developed by Van Eck and Waltman (Leiden, The Netherlands). The results show the exponential growth of this topic, although there seems to be no consensus regarding its definition, conceptualization and measurement. Concerning its conceptual development, GHRM seems to currently fit the second stage of development (evaluation and augmentation) of Reichers and Schneider’s three-stage model of the evolution of constructs. Future research seems to point in the direction of establishing the barriers separating GHRM from other human resource management topics, defining green practices and determining the antecedents and consequences of GHRM.

Introduction

     The economic growth of the last two centuries has represented prosperity and longevity for humanity. However, the impact of various industrial practices, reflected in pollution and the accumulation of waste and residues, is increasingly evident (IPCC 2018; Jackson et al. 2011). Climate change represents a new set of challenges, altering competitive and regulatory spheres, indirectly through global policy efforts to curb carbon emissions, and directly as a means of combating the unravelling consequences of extreme weather events (IPCC 2018). By invoking unprecedented changes in socio-economic systems, climate change makes it urgent for society to prepare and adapt in the face of new contingencies (Winn et al. 2011). With increasing regulatory and public pressure, more and more business entities are proactively implementing practices and strategic changes, such as investing in low-CO2 technologies and renewable energy, in order to transition to environmental sustainability (González-Benito and González-Benito 2006; IPCC 2018).

     The multidisciplinarity required to reduce organizational environmental footprints challenges the vision that this theme is restricted to environmental sciences, causing new fields of study to emerge in the areas of social research and management (Shrivastava and Berger 2010). In this sense, several related topics have been increasingly emphasized: corporate social responsibility (CSR), environmental management (EM), business ethics, socially responsible consumption and sustainability strategies, among others (Schuler et al. 2017; Shrivastava and Berger 2010).

Conclusions and Future Directions

     The bibliometric analysis of the literature produced between 2010 and 2020 highlights the importance of GHRM today as an expanding field, particularly from the second half of the decade. The purpose of GHRM is to actively participate in the creation of greener societal paths and respond to environmental and ecological issues from the organizational context. This HRM specialty refers to one of the most important challenges faced by humanity

     By mapping the existing literature streams—implementation of GHRM as a strand of EM, consequences at the organizational level and consequences at the employee level— tracing their contributions and development in the last decade, and identifying the construct development stage, this paper has met its objectives. In short, the results obtained suggest that the implementation of green practices in organizations will be reflected in lower levels of environmental pollution and contamination. Despite the emphasis on the repercussions of GHRM at work, it goes beyond the labor sphere, since green environmental values are transferable from context to context, i.e., green behaviors applied at work are reflected in personal life and vice versa. The fact that the evolution of the construct has been going beyond a concept focused only on EM demonstrates the consideration of employees endowed with unique strategic value and their decisive role in organizational sustainability. The resource-based view (Barney 1991) is a theoretical contribution that points in this direction (Yusliza et al. 2017).