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In response to the worsening environmental crisis, there have been multiple calls for sustainable supply chain management (SSCM) scholars and practitioners to adopt a “business-not-as-usual” approach based on justice, fairness, equity and sustainability. We add to this literature by proposing environmental justice (EJ) as a key concept for the theory and practice of SSCM.

This conceptual article builds SSCM theory on EJ and contributes to supply chain justice research and practice by introducing the concept of the “environmentally just supply chain” and presenting pathways for operationalizing it in practice.

Three pathways are proposed to leverage transformative SSCM to create environmentally just supply chains: human rights due diligence, resilience thinking and coproduction of environmentally just supply chains.

The three pathways can be used by actors within a supply chain to create environmentally just supply chains.

This article extends transformative, non-instrumental perspectives on environmental sustainability within SSCM scholarship to provide insights into how supply chains can be transformed through EJ. Not only does the article show the relevance of EJ for SSCM theory and practice, but it elaborates pathways for moving from harm reduction to transformative sustainability actions.

The circular economy (CE) has become increasingly popular in recent years due to its potential in combining the economic growth positively with businesses, society and the environment simultaneously. The purpose of this review is to provide a concise summary of the existing literature regarding how CE strategies can help mitigate climate change.

A comprehensive review of extant literature is undertaken on the topic of CE and climate change. Six sectors are explored in this chapter; although these sectors are different, but still, they are interdependent and are not completely separate.

Thorough study of literature reveals that the energy, transport and manufacturing sectors have the greatest potential for reducing greenhouse gas emissions, while the waste and building sector have a moderate potential for savings. The agriculture sector, on the other hand, is predicted to have the lowest potential for savings.

This chapter provides implications for achieving a sustainable future in terms of economic growth, social harmony and environment conditions by developing efficient and affordable methods to achieve the goal of CE.

This chapter is a unique endeavour to explore the intricate relationship between CE and climate change. Although both concepts have been explored individually by various studies, but our study is one of the few attempts made to emphasise the crucial role of CE to mitigate the climate change.

The study aims to determine the impact of perceptual and attitudinal factors on employees’ counterproductive work behaviour (CWB). The study emphasises the verification of the direct, indirect, linear and non-linear effects of several antecedents of CWBs. The moderating role of self-efficacy is also investigated.

Data were collected from 1,215 employees from several industrial companies in Southern Iraq. The study used the hybrid approach to data analysis, based on a dual-stage SEM-ANN, i.e. partial least squares structural equation modelling and artificial neural network approach.

Results indicate that most of the proposed variables predict CWB and that abusive supervision and perceived organisational politics (POP) positively affect job burnout (JB) through job stress. In addition, non-linear relationships, JB, abusive supervision and POP are the most important in predicting CWB. The study confirms that a negative perception of the work environment increases the likelihood of harmful behaviours in the organisation and that self-efficacy can reduce such a perception.

The importance of the current study is summarised in its attempt to verify the antecedents of CWB by relying on a two-step approach to test linear and non-linear relationships. This approach will greatly enhance theories regarding adverse behaviour in the workplace, especially, with a fairly large sample size.

The effects of gendered views on employee voice are of great importance for knowledge sharing within public universities. Yet, they are still neglected by current human resource management and entrepreneurship literature. While strengthening themselves by reinforcing the strengths and opportunities, public universities can generate entrepreneurial opportunities through various knowledge-sharing mechanisms, including social networks and employee voice. This became a crucial lever for public universities to leverage competitive advantages and to support entrepreneurial activities through network knowledge-based sharing. For this purpose, this study aims to examine the various aspects of entrepreneurship via the voice of employees, emphasizing the moderating effect of gender and the mediating role of social networks on the link between employee voice and the entrepreneurial atmosphere of universities.

The authors collected survey data from a cross-sectional sample of 335 employees engaged in entrepreneurship activities within public universities in an emerging economy context and analyzed the data using partial least squares structural equation modeling (PLS-SEM) with the Smart-PLS software.

The PLS-SEM analysis found that different dimensions of the university entrepreneurial climate (communication, knowledge sharing and innovative climate) positively impact members’ voices within public universities. This effect is amplified by social networks, which are crucial for spreading knowledge among faculty, thereby fostering a more open and collaborative academic environment.

When acting, the university top management team should encourage the generation and dissemination of entrepreneurial ideas to nurture a dynamic entrepreneurial atmosphere and social involvement, ultimately supporting sustainable competitive advantages through a culture of strategic knowledge sharing. The results have practical implications for university managers, entrepreneurship education actors, administrators, policymakers and entrepreneurial ecosystem actors, by demonstrating how social networks can amplify the dissemination of ideas and entrepreneurial spirit.

This research explores how entrepreneurship and social networks can help faculty members have a stronger influence in academic settings. It also fills in the gaps in knowledge about how human resource management and entrepreneurship can work together to create a more communicative and innovative academic environment. Additionally, this study brings new ideas to existing literature by looking at how gender differences can affect employee voice, particularly emphasizing the importance of women in leadership roles at universities. This study is also the first to delve into how entrepreneurship and social networks, along with gender perceptions, play a role in shaping the voice of employees in a public university.

Companies seek to increase the percentage of acquisitions in different parts of the world by expanding operations. Many companies are adopting strategic mergers to expand their influence. However, most strategic change programs fail to achieve their objectives. This study aims to investigate employees’ reactions after strategic mergers through the mediating role of the employees’ psychological context. It was necessary to identify the most prominent postmerger employees’ behaviors. The study addressed this gap by investigating the outcomes of strategic mergers.

Data for this study were collected from 30 family businesses. Accordingly, 341 questionnaires were collected with an overall response rate of 64%. The structural equation modeling (PLS-SEM) approach and the nonlinear relationships approach were adopted by implementing artificial neural network (ANN) analysis.

The results confirm that there is a clear impact of strategic mergers on employees’ postmerger behavior because of the change at the hierarchical level and the process of distributing roles. Employees’ psychological context (individual incentives, anxiety and individual mobbing) mediates the relationship between strategic mergers and postmerger employees’ behavior. In addition, individual incentives are considered the main contributor to retaining or not retaining employees in family businesses after strategic merger.

Policymakers in organizations must pay attention to employees’ possible reactions to the internal and external policies of the organization by increasing individual incentives and reducing individual mobbing toward strategic merger. This study has theoretical implications that are critical guidelines for academics in mitigating the negative consequences for employees’ postmerger behavior. This study captured linear and nonlinear relationships to discover the determinants and antecedents of a strategic merger in family businesses. However, future studies should focus on using more robust statistical methods by adopting decision-making methods to determine the best and worst companies in terms of adopting strategic mergers.

The scarcity of literature on the most important determinants of postmerger employees’ behavior is considered an encouragement to conduct the current study. To this end, this study enriches the ongoing and future literature by examining the most important factors influencing the strategic merger of family businesses. Family businesses have changed the economic landscape of many countries. The investigation of the strategic merger of these companies is considered a worthy matter of study to improve the nation’s economy.

With the current developments within the sphere of Internet of Things (IoT) technology, many conventional articles are all being fitted with smart functionalities, ranging from chairs, beds, shoes and caps to underwear. Bags which are utility as well as fashion items have not been left out of this smart craze, albeit to a less popular degree. The purpose of this study is to fill the research gap on the subject of smart bags research and applications and to contribute to the general discourse on IoT.

This study adopts literature search and database review, concept mapping as well as synthesis methodologies. Relevant literature form databases such as Web of Science, Google Scholar and Bing Scholar were interrogated. Manual sifting was done to eliminate papers that do not fit the set inclusion criteria. Literature on smart bags was organized into structured frameworks using concept mapping methodology. Applying a synthesis methodology enabled an exploration of the different technological trends in smart bag research and their areas of application.

The study identified about 15 different smart bag applications and functionalities. Discussed in this study is a classification of bags based on a number of points such as way of carrying, size, utility and fabrication materials. Also discussed are the description of what constitute a smart bag, relevant technologies for smart bag design and engineering and subsequently the current trends in smart bag applications. This study also discovered that the air travel industry tend to have some difficulties with this smart bag technologies, specifically with their built-in batteries.

The results of this study will provide researchers and other stakeholders with key information about existing problems and opportunities in smart bag research and applications. This will go a long way to help in guiding future research as well as policymaking in smart bag design and application.

To the best of the authors’ knowledge, this is the first review on the subject of smart bags even though smart bag research and commercial product design continue to gain momentum in recent years.

Economists and governments worldwide are largely concerned about sustainability, CO₂ footprint and climate change, which are mostly caused by fossil fuel emissions. This study aims to provide an in-depth analysis of the significant role played by renewable energy (RE) sources in generating clean energy for achieving sustainable net-zero standards and mitigating climate change.

A thorough review of literature was conducted on the topic to provide insights into the existing state about the adoption of RE sources to achieve the net-zero goals.

As a result of the extensive review, it is found that all forms of RE, such as hydropower, solar energy, wind energy, bioenergy and geothermal power, are currently being used in many countries. Also, application of these sources across various sectors and their environmental consequences also vary for each RE source.

This chapter emphasises that adoption of RE sources is crucial to reduce the usage of limited fossil-based natural resources, which have significant negative effects on the environment. The adoption of RE at large scale requires the implementation of new regulations and policies along with technological progress for enhancing the affordability and effectiveness of these sources.

This chapter provides compelling evidence to support the acceleration of the transition from a vulnerable fossil fuel–dependent economy to a sustainable low-carbon one, with RE sources playing a central role.

This study aims to investigate stakeholders' perception of the most prevalent unethical practices in the Ghanaian construction industry.

Data used for this study came from a cross-sectional survey (questionnaire), which was administered to 273 stakeholders in the construction industry using convenience sampling technique. The data were analyzed using statistical software package SPSSv17 to determine the most prevalent unethical practices. The ranking factor was calculated based on relative importance index (RII) value.

The results of this study reveal that corruption was perceived by major stakeholders as the most prevalent unethical behavior (RII = 0.82) followed by bribery (RII = 0.79). Political interference and kickback came third (RII = 0.77) and fourth (RII = 0.74), respectively. However, the least prevalent unethical behaviors were extortion (RII = 0.56), workplace violence (RII = 0.57), alcohol abuse (RII = 0.59) and harassment (RII = 0.59). The findings suggest that when the various groupings were taken into consideration separately, the differences in their perceptions were obvious.

Data for this study were collected from construction stakeholders in Ghana who were conveniently sampled. As a result, in reference to the sampling framework which focused on major stakeholders in only two regions of Ghana does not sufficiently ensure full generalization of the results.

The findings of the study provide significant information for construction organizations and practitioners regarding unethical practices, which are most prevalent in the Ghanaian construction industry. Construction organizations and practitioners seeking to mitigate the negative effect of unethical practices on their performance should focus on educating construction workers on how to avoid corrupt practices and report same to the authorities. Also, ethics training programs must be instituted for staff coupled with constant and random inspection and checking of ethical compliance, verbal promotion and praise for ethical conduct and in some cases increase in employees pay.

This paper is one of the first to have accessed the views of broader stakeholders, i.e. consultants, contractors, professionals, suppliers, regulators, clients and construction workers in the construction industry regarding the most prevalent unethical practices in the Ghanaian construction industry in one study. This study, therefore, enriches the current literature by providing additional dimension to the understanding of unethical practices in the Ghanaian construction industry.

The present study aimed to explore the consequences of perceived authenticity in artificial intelligence (AI) assistants and develop a serial-mediation architecture specifying causation of loyalty in human–AI relationships. It intended to assess the predictive power of the developed model based on a training-holdout sample procedure. It further attempted to map and examine the predictors of loyalty, strengthening such relationship.

Partial least squares structural equation modeling (PLS-SEM) based on bootstrapping technique was employed to examine the higher-order effects pertaining to human–AI relational intricacies. The sample size of the study comprised of 412 AI assistant users belonging to millennial generation. PLS-Predict algorithm was used to assess the predictive power of the model, while importance-performance analysis was executed to assess the effectiveness of the predictor variables on a two-dimensional map.

A positive relationship was found between “Perceived Authenticity” and “Loyalty,” which was serially mediated by “Perceived-Quality” and “Animacy” in human–AI relational context. The construct “Loyalty” remained a significant predictor of “Emotional-Attachment” and “Word-of-Mouth.” The model possessed high predictive power. Mapping analysis delivered contradictory result, indicating “authenticity” as the most significant predictor of “loyalty,” but the least effective on performance dimension.

The findings of the study may assist marketers to understand the relevance of AI authenticity and examine the critical behavioral consequences underlying customer retention and extension strategies.

The study is pioneer to introduce a hybrid AI authenticity model and establish its predictive power in explaining the transactional and communal view of human reciprocation in human–AI relationship. It exclusively provided relative assessment of the predictors of loyalty on a two-dimensional map.