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With big data (BD), traditional supply chain is shifting to digital supply chain. This study aims to address the issues and challenges in the way toward the implementation of big data analytics (BDA) in sustainable supply chain management (SSCM).

The factors that affect the implementation of BDA in SSCM are identified through a widespread literature review. The PESTEL framework is used for this purpose as it covers all the political, economic, social, technological, environmental and legal factors. These factors are then finalized by means of experts' opinion and analyzed using structural equation modeling (SEM).

A total of 10 factors are finalized with 31 sub-factors, of which sustainable performance, competitive advantage, stakeholders' involvement and capabilities, lean and green practices and improvement in environmental performance are found to be the critical factors for the implementation of BDA in SSCM.

This research has taken up the case of Indian manufacturing industry. It can be diversified to other geographical areas and industry sectors. Further, the quantitative analysis may be undertaken with structured or semi-structured interviews for validation of the proposed model.

This research provides an insight to managers regarding the implementation of BDA in SSCM by identifying and examining the influencing factors. The results may be useful for managers for the implementation of BDA and budget allocation for BDA project.

The result includes green practices and environmental performance as critical factors for the implementation of BDA in SSCM. Thus the research establishes a positive relationship between BDA and sustainable manufacturing that ultimately benefits the environment and society.

This research addresses the challenges in the implementation of BDA in SSCM in Indian manufacturing sector, where such application is at its nascent stage. The use of PESTEL framework for identifying and categorizing the factors makes the study more worthwhile, as it covers full spectrum of the various factors that affect the strategic business decisions.

The competition in the academe has always been tough, but today, the academe seems to be more like an industry than an academic community as academics are evaluated through quantified and economic means.

This article leans on Heidegger’s thoughts on the essence of technology and his ontological view on being to show the dangers that lie in this quantification of researchers and research.

Despite the benefits that information systems (ISs) offer to people and research, it seems that technology has made it possible to objectify researchers and research. This has a negative impact on the academe and should thus be looked into especially by the IS field, which should note the problems that exist in its core. This phenomenon of quantified academics is clearly visible at academic quantification sites, where academics are evaluated using metrics that count their output. It seems that the essence of technology has disturbed the way research is valued by emphasising its quantifiable aspects. The study claims that it is important to look for other ways to evaluate researchers rather than trying to maximise research production, which has led to the flooding of articles that few have the time or interest to read.

This paper offers new insights into the current phenomenon of quantification of academics and underlines the need for critical changes if in order to achieve the academic culture that is desirable for future academics.

The potential growth in cryptocurrencies has raised serious ethical and religious issues leading to a new investment rethinking. This paper aims to identify the influence of religiosity on cryptocurrency acceptance through an extended technology acceptance model (TAM) model.

In the first phase, this research develops a conceptual model that extends the theory of the TAM by integrating the religiosity component. In the second phase, the proposed model is tested using search volume queries in daily frequencies from 01/01/2018 to 31/12/2022 and structural equation modeling (SEM).

The empirical results demonstrate a significant positive effect of religiosity on the intention to use cryptocurrency, the users' perceived usefulness (PU) and ease of use (PEOU). Besides, the authors note that PEOU positively influences the intention. Furthermore, religiosity indirectly affects the intention through the PEOU and positively impacts the intention through the PU. In the same way, PEOU has a considerable indirect effect on the intention through PU.

This study has practical and theoretical contributions by providing insights into the cryptocurrency acceptance factors. In other words, it contributes to the literature by extending TAM models. Practically, it helps managers determine factors affecting the intention to use cryptocurrencies. Therefore, they can adjust their industry according to the suitable characteristics for creating successful projects.

Identifying the effect of religiosity on cryptocurrency users' choices and decisions has a social added value as it provides an understanding of the evolution of psychological variants.

The findings emphasize the importance of integrating big data to analyze users' attitudes. Besides, most studies on cryptocurrency acceptance are investigated based on one kind of religion, such as Christianity or Islam. Nevertheless, this paper integrates the effect of five types of faith on the users' intentions.

This study aims to examine the relationship between the environment and tourism flows, as well as the economic variables of the 32 states of Mexico for the period 1999–2019 based on data availability. The related literature studying tourism and environmental impacts is scarce at a national level, with most of them being local case studies. Some international studies find that if the relationship exists, it is weak or nonexistent, using CO₂ as a proxy in most cases.

The present study uses panel data and cointegration panel methodologies, while also using geographic information systems to observe the distribution of variables at a state level between tourism and environmental variables.

The findings of the study are as follows: state gross domestic product, the inertia of environmental variables (i.e. volume of water treatment and solid waste), occupied rooms (proxy variable for tourism activity) and average temperature have an impact on the contemporary evolution of environmental variables; national and international tourist variables have no impact on the environment; the panels are integrated in such a way that there is a long-term equilibrium between states and some environmental care variables; and no conclusive evidence is found regarding the impact of tourism activity on the considered environmental variables.

The main limitations and areas of opportunity of the work refer to the amount of data available over time and the precision of the measurement of the variables. The availability, temporality and frequency of the data are also limitations of the research. An example of this is the nonexistence of CO₂ emissions at the state level. Additionally, studying other countries and regions for which there are limitations of data and applied studies is also a challenge.

The results are important for economies (in growth) and societies whose economic growth depends on tourism flows and have done little to reverse the damage that tourism has on the environment.

The models can contribute to study the relation between tourism and environmental variables and could be extended to regions, states and provinces for decision-making on actions to be taken for the present and future.

The originality of the research is innovative for the region: Mexico, Central and Latin America. There are no works that have studied these problems with this methodology and these variables. In terms of originality, the classic models of panel data and cointegration of panel data are useful and easily replicable for others to use for different countries. The results are relevant because there is apparently no relationship between tourism and some environmental variables in the short run, but there exists a weak and strong long-run relation between some of them.

本研究采用面板数据和协整面板模型方法, 同时利用地理信息系统(gis)观察州一级层面旅游和环境方面的变量分布。

本研究根据数据可用性, 研究了墨西哥32个州1999–2019年期间环境与旅游流量及经济变量之间的关系。在国家层面上研究旅游与环境影响的相关文献很少, 而且大多是地方的个案研究。一些国际研究发现, 即使有这种关系, 大多数案例中使用二氧化碳作为替代变量, 这种关系也是很弱或不存在。

i)国家国内生产总值, 环境变量的惯性(即水处理量和固体废物量), 占用的房间(旅游活动的代理变量)和平均温度对环境变量的现有演化有影响。ii)国内和国际旅游变量对环境没有影响。iii)面板数据以这样一种方式集成, 即国家和一些环境变量之间存在一种长期平衡。iv)关于旅游活动对所考虑的环境变量的影响没有确凿的证据。

这项工作的主要局限和机会领域是指随着时间的推移可获得的数据量和变量测量的精度。数据的可用性、时效性和频率也是本研究的局限性。这方面的一个例子是在州一级不存在二氧化碳排放。此外, 由于数据和应用研究的局限, 研究其他国家和地区也是一个挑战。

研究结果对经济增长依赖旅游业流量的经济体和社会具有重要意义, 这些经济体和社会对扭转旅游业对环境的破坏方面做得还不够。

这些模型有助于研究旅游业与环境变量之间的关系, 并可推广到地区、州和省, 以制定当前和未来的行动决策。

这项研究的原创性对该地区(墨西哥、中美洲和拉丁美洲)来说是具有创新性的。没有人用这种方法和这些变量研究过这些问题。就原创性而言, 面板数据和面板数据协整的经典模型是有用的且易于复制, 可供其他国家使用。 研究结果具有一定的相关性, 因为旅游业与部分环境变量在短期内不存在明显的相关性, 但在它们中的一些变量在长期内存在着或强或弱的相关性。

Se examina la relación entre medio ambiente y flujos turísticos, así como variables económicas de los 32 estados de México para el período 1999-2019 basado en la disponibilidad de datos. La literatura relacionada que estudia el turismo y los impactos ambientales es escasa a nivel nacional, siendo la mayoría de ellos estudios de casos locales. Estudios internacionales encuentran que, si la relación existe, es débil o inexistente, utilizando el CO2 como un indicador en la mayoría de los casos.

Se utilizaron metodologías de datos de panel y cointegración de panel, además sistemas de información geográfica para observar la distribución de variables a nivel estatal.

i) El Producto Interno Bruto Estatal, la inercia de las variables ambientales (es decir, volumen de tratamiento de agua y residuos sólidos), habitaciones ocupadas (proxy de la actividad turística) y temperatura promedio tienen un impacto en la evolución contemporánea de las variables ambientales, ii) las variables turísticas nacionales e internacionales no tienen un impacto en el medio ambiente, iii) los paneles están integrados de tal manera que existe un equilibrio a largo plazo entre turismo, crecimiento económico y algunas variables ambientales, y iv) no se encuentra evidencia concluyente con respecto al impacto de la actividad turística en las variables ambientales consideradas.

Las principales limitaciones y áreas de oportunidad del trabajo se refieren a la cantidad de datos disponibles en el tiempo y a la precisión de la medición de las variables. La disponibilidad, temporalidad y frecuencia de los datos también son limitaciones de la investigación. Un ejemplo de ello es la inexistencia de emisiones de CO2 a nivel estatal. Además, el estudio de otros países y regiones para los que existen limitaciones de datos y estudios aplicados también es un reto.

Los resultados son importantes para las economías (en crecimiento) y las sociedades cuyo crecimiento económico depende de los flujos turísticos y que han hecho poco por invertir los daños que el turismo produce en el medio ambiente.

Los modelos pueden contribuir a estudiar la relación entre el turismo y las variables medioambientales y podrían extenderse a regiones, estados y provincias para la toma de decisiones sobre las acciones a emprender para el presente y el futuro.

El artículo proporciona un análisis innovador y exploratorio hacia una perspectiva futura que agrega valor al turismo y la planificación para la sostenibilidad. La relación entre turismo y medio ambiente se ha estudiado durante varios años. La UNTWO ha abordado las consecuencias del turismo en el medio ambiente, particularmente, más basura, mayor consumo de agua, emisiones de CO2 y otros aspectos. Pocos trabajos estudian la relación entre estas variables.

La originalidad de la investigación es innovadora para la región: México, América Central y América Latina. No existen trabajos que hayan estudiado estos problemas con esta metodología y estas variables.

En términos de originalidad, los modelos clásicos de datos de panel y cointegración de datos de panel son útiles y fácilmente replicables para que otros los utilicen en diferentes países.

Los resultados son relevantes porque aparentemente no hay una relación entre el turismo y algunas variables ambientales a corto plazo, existe una relación débil y fuerte a largo plazo entre algunas de ellas.

This study aims to observe and discuss an emerging disintermediation in transportation, finance and health care, and explain how these three key areas depend on intermediary institutions that are the fruit of modern corporate governance conditions that find their roots in classical sociological theory.

The authors review and incorporate a diversity of research literature to explain the likelihood for the development and continuation of disintermediation.

The authors map two sociological perspectives (Emile Durkheim’s theory of interdependence and Herbert Spencer’s theory of contracts) to two modern corporate governance theories (resource dependence theory and agency theory). The authors then discuss the challenging social situation resulting from modern corporate governance and show how these conditions create the potential for a continuum of disintermediation across the specific and crucial economic sectors of transportation, finance and health care.

The implications of this theoretical integration can help organizational leaders navigate complex social and strategic issues and prepare for the consequences that may result from the emerging disintermediation.

This study aims to analyse how the adoption of Industry 4.0 technologies can help different types of agri-food supply chains introduce and manage innovations in response to the challenges and opportunities that emerged following the COVID-19 pandemic.

A systematic literature review methodology was used to bring together the most relevant contributions from different disciplines and provide comprehensive results on the use of I4.0 technologies in the agri-food industry.

Four technological clusters are identified, which group together the I4.0 technologies based on the applications in the agri-food industry, the objectives and the advantages provided. In addition, three types of agri-food supply chains have been identified and their configuration and dynamics have been studied. Finally, the I4.0 technologies most suited for each type of supply chain have been identified, and suggestions on how to effectively introduce and manage innovations at different levels of the supply chain are provided.

The study highlights how the effective adoption of I4.0 technologies in the agri-food industry depends on the characteristics of the supply chains. Technologies can be used for different purposes and managers should carefully consider the objectives to be achieved and the synergies between technologies and supply chain dynamics.

This study aims to assess the alignment of South Korea’s government-certified social enterprises (GCSEs) with prevailing social enterprise (SE) models, notably the entrepreneurial nonprofit, social cooperative and social business models delineated in the “Emergence of Social Enterprises in Europe” (Defourny and Nyssens, 2012, 2017a, 2017b) and the “principle of interest” frameworks (Defourny et al., 2021). Thereby, it seeks to situate these enterprises within recognized frameworks and elucidate their hybrid identities.

Analyzing panel data from 2016 to 2020 for 259 GCSEs, this study uses tslearn for k-means clustering with dynamic time warping to assess their developmental trajectories and alignment with established SE models, which echoes the approach of Defourny et al. (2021). We probe the “fluid” identities of semi-public sector SEs, integrating Gordon’s (2013) notion that they tend to blend various SE traditions as opposed to existing in isolation.

Results indicate that GCSEs do align with prevalent SE frameworks. Furthermore, they represent a spectrum of SE models, suggesting the versatility of the public sector in fostering diverse types of SEs.

The concept of a semi-public sector SE model has been relatively uncharted, even though it holds significance for research on SE typologies and public sector entrepreneurship literature. This study bridges this gap by presenting empirical evidence of semi-public SEs and delineating the potential paths these enterprises might take as they amalgamate various SE traditions.

Algorithms are widely used to manage various activities in the gig economy. Online car-hailing platforms, such as Uber and Lyft, are exemplary embodiments of such algorithmic management, where drivers are managed by algorithms for task allocation, work monitoring and performance evaluation. Despite employing substantially, the platforms face the challenge of maintaining and fostering drivers' work engagement. Thus, this study aims to examine how the algorithmic management of online car-hailing platforms affects drivers' work engagement.

Drawing on the transactional theory of stress, the authors examined the effects of algorithmic monitoring and fairness on online car-hailing drivers' work engagement and revealed the mediation effects of challenge-hindrance appraisals. Based on survey data collected from 364 drivers, the authors' hypotheses were examined using partial least squares structural equation modeling (PLS-SEM). The authors also applied path comparison analyses to further compare the effects of algorithmic monitoring and fairness on the two types of appraisals.

This study finds that online car-hailing drivers' challenge-hindrance appraisals mediate the relationship between algorithmic management characteristics and work engagement. Algorithmic monitoring positively affects both challenge and hindrance appraisals in online car-hailing drivers. However, algorithmic fairness promotes challenge appraisal and reduces hindrance appraisal. Consequently, challenge and hindrance appraisals lead to higher and lower work engagement, respectively. Further, the additional path comparison analysis showed that the hindering effect of algorithmic monitoring exceeds its challenging effect, and the challenge-promoting effect of algorithmic fairness is greater than the algorithm's hindrance-reducing effect.

This paper reveals the underlying mechanisms concerning how algorithmic monitoring and fairness affect online car-hailing drivers' work engagement and fills the gap in the research on algorithmic management in the context of online car-hailing platforms. The authors' findings also provide practical guidance for online car-hailing platforms on how to improve the platforms' algorithmic management systems.

This paper aims to provide an examination of the use of the concept of resilience and its use in service organisation, ecosystem-related literature and the wider social sciences.

This paper provides a critical review and commentary on the resilience literature in the social and business sciences and its relevance to service organisations.

Two main approaches towards resilience are identified (engineering and socio-ecological resilience) with each having different assumptions about the nature of resilience with corresponding implications for policymaking, indicator selection and application in a service context. These approaches operate at different scales and possess different properties with respect to the likelihood of enacting transformative service marketing.

Different conceptualisations of resilience have profound implications for resilience-related policymaking as well as understanding change and adaptation in service ecosystems and organisations.

The transformative possibilities of resilience are connected to the active enhancement and construction of social capacity by service organisations and the persistent resilience of the resilience concept.

This paper highlights the importance of clearly defining the resilience concept and its implications for research and transformative service organisations.