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Small business enterprises (SBEs) are a very critical element of the micro, small and medium enterprises (MSME) sector especially in the underdeveloped locations of the country. SBEs not only provide employment but also support the local economy by way of their products and services. In modern times, their presence on the digital platform is becoming essential and thus, these types of studies are required to bring to the table the issues and practices from the less represented sections of the sector. This study attempts to understand the responsiveness of the SBEs in Sikkim, India, and Bhutan in terms of their frequency of digital marketing (DM) usage. This study also attempts to understand the relationship between the factors affecting the practice or adoption of DM among the SBEs of Bhutan and Sikkim, India. For this purpose, empirical data were gathered from 320 SBEs from Sikkim and Bhutan representing the various sectors as defined by the national governments of the two countries. The SBEs of Bhutan and Sikkim are not found to be very active on the front of DM. The SBEs in these two locations need to become more active in using the digital platforms and tools to promote their products and services. The industry trends and government support in the form of infrastructural development are expected to play a vital role in orienting the SBEs into the adoption of DM in a better way. This study is crucial for the MSME sector, the government, telecom services providers, and local entrepreneurs.

Halal logistics play a crucial role in maintaining a product’s “halal integrity” from farm to fork. These logistics operations are exposed to risks during transportation, storage and handling, that negatively affect the halal supply chain’s operational efficiency and integrity. Therefore, the main purpose of this research is to propose a risk assessment framework for halal logistics.

Initially, the risks associated with halal logistics are identified through an extensive literature review, and then the significant ones are validated with the expert’s input. After that, an appropriate multicriteria decision-making method named best worst method (BWM) is used to prioritise the identified risks. Finally, the robustness of the obtained ranking is assessed with sensitivity analysis.

This research identifies 26 halal logistics risks and then categorises these risks into 6 significant dimensions and proposes a framework. The result obtained from the BWM analysis shows that organisational, transportation and design risks are the primary risks present in halal logistics. Among the halal logistics risks, partnership risk, risk of contamination during transportation and risks of unskilled workers are the top three halal logistics risks that need to be addressed on a priority basis for maintaining halal integrity. Furthermore, this study also suggests some valuable suggestions for mitigating these risks that the logistics providers could use.

The proposed framework is helpful for the assessment of risks associated with halal logistics. The prioritisation of the identified risks supports the managers in formulating mitigation strategies that might reduce the effect of these associated risks in logistics operations.

This study focusses on halal logistics, and to the best of authors’ knowledge, this may be the first attempt to systematically examine the risks related to halal logistics.

Mentoring is an intense relationship between a senior experienced individual who is the mentor and a less experienced individual who is the protégé. Mentors provide counselling, guidance, advice, support and feedback for the protégé's personal and professional development. With the well-being of the family as the central issue in family firms, mentoring is often seen to be akin to a parent–child relationship. In Bangladesh, paternalistic and informal parental mentoring is the norm for grooming children both morally and professionally. Using six caselets of large family firms of Bangladesh, this chapter provides insight into the paternalistic style of mentoring, and also the generational differences in mentoring between the firm's owner and his successor.

Amid rising environmental concerns, Industry 4.0 and blockchain technology (BCT) are transforming circular economy practices and prevailing business models. Recognizing the same, the current study examines the role of advanced technology in circular practices and their impact on eco-environmental performance, which influences organizational performance. The study collects data from 185 food processing enterprises that are located in Malaysian territories. By employing CB-SEM modeling, the study provides three key findings. First, Industry 4.0 significantly improves the circular economy practices. Second, circular economy practices help to improve firms' environmental performance but did not stimulate operational performance. Third, higher eco-environmental performance significantly boosts organizational performance. This study set out the foundations for participating countries/firms that help to achieve sustainable goals through the integration of blockchain technology in circular economy practices.

The garments/textiles industry is the second most polluting industry in the world. However, efforts to understand and curtail its adverse environmental impacts have not been commensurate, and previous works have largely been fragmented and disjointed. This study aims to coduct a comprehensive and systematic green supply chain management (GSCM) investigation on this industry, where a multidimensional framework involving green supply chain practices and performance is developed, validated and applied.

A framework consisting of 12 constructs (8 on practices and 4 on performance) and their underlying measures were developed through an extensive literature review. A survey methodology was used to obtain responses from 403 garment-manufacturing firms in Bangladesh, one of the leading garment producers in the world. Confirmatory factor analysis and structural equation modeling were used first to validate the first- and second-order constructs and then test the hypothesized relationships.

Internal environmental management and cooperation with stakeholders were identified as necessary precursors for implementing the second-order green supply chain practices comprising green design, green purchasing, green manufacturing, green transportation, green facilities and end-of-life management. The implementation of green supply chain practices was found to have a (direct) positive impact on environmental, economic and operational performance and an indirect positive impact on organizational performance. Similarly, both economic and operational performance was found to impact organizational performance positively. Surprisingly, a negative relationship (albeit low) was observed between environmental and organizational performance. Also, garment-manufacturing firms were found to have been unable to translate their IEM capabilities into strategic and long-term cooperation with stakeholders.

The study fills a gap in the literature about applying/implementing GSCM in the garment industry. Future studies in the garment industry and elsewhere could utilize the framework to understand further the synergistic impact of green supply chain practices on performance.

The findings provide practitioners, policymakers and organizations associated with the garment industry with critical insights on the various opportunities and challenges in adopting GSCM. Also, the positive impact of green supply chain practices on performance could provide the impetus for manufacturing firms to adopt GSCM.

A comprehensive GSCM investigation on the garment industry has not been previously attempted and constitutes the novelty of this work. Also, Bangladesh is the second-largest garment exporter worldwide, making this study contribution even more valuable.

The complex network structure causes several disruptions in the supply chain that make risk management essential for supply chain management including halal supply chain (HSM). During risk management, several challenges are associated with the risk assessment phase, such as incomplete and uncertain information about the system. To cater this, the authors propose a risk assessment framework that addresses the issues of uncertainty using neutrosophic theory and demonstrated the applicability of the proposed framework through the case of halal supply chain management (HSCM).

The proposed framework is using the capabilities of the neutrosophic number which can handle uncertain, vague and incomplete information. Initially, the risk related to the HSC is identified through a literature review and expert’s input. Further, the probability and impact of each HSM-related risk are assessed using experts’ input through linguistic terms. These linguistic values are transformed into single-value trapezoidal neutrosophic numbers (SVTNNs). Finally, the severity of each HSM-related risk is determined through the multiplication of the probability and impact of each risk and prioritised the risks based on their severity.

A comprehensive risk assessment framework is developed that could be used under uncertainty. Initially, 16 risks are identified related to the HSM. Further, the identified risks are prioritised using the severity of the risks. The high-priority risk is “raw material status”, “raw material wholesomeness” and “origin of raw material” while “information integrity” and “people integrity” are low-priority risks.

HSM risk can be effectively assessed through the proposed framework. The proposed framework applied neutrosophic numbers to represent real-life situations, and it could be used for other supply chains as well.

The proposed method is effectively addressing the issue of linguistic subjectivity, inconsistent information and uncertainty in the expert’s opinion. A case study of the HSC is adopted to illustrate the efficiency and applicability of the proposed risk framework.

This paper aims to examine the effects of corporate social responsibility (CSR) on customer orientation and competitive advantage.

Data were collected from 368 retail banking customers in Pakistan and analysed using partial least squares-based structural equation modelling.

Firstly, the research findings indicate that CSR has a positive and significant effect on customer orientation. Secondly, CSR and customer orientation were found to be the antecedents of competitive advantage.

Managers can use CSR activities strategically to enhance the perceptions of a firm’s customer orientation in their minds. This can then lead towards achieving a competitive advantage over rivals. The trend of being socially responsible, as well as customer-orientated, can lead to a healthy ecosystem within the industry, which in turn will benefit its stakeholders.

Firstly, this is one of the pioneering studies that investigate the relationship between CSR and customer orientation. Secondly, it examines the under-explored roles of CSR and customer orientation as antecedents of competitive advantage.

Knowledge management (KM) is an important topic in the age of big data, and this study adds to the existing body of literature by providing a novel KM perspective on the technological phenomenon of artificial intelligence (AI). This study aims to discover how AI might facilitate knowledge-based business-to-business (B2B) marketing. In this chapter, the authors take a close look at the building blocks of AI and the relationships between them. Future research directions and also the effects of the various market information building components on B2B marketing are discussed. The study’s approach is theoretical; it tries to provide a framework for characterising the phenomenon of AI and its constituent parts. Additionally, this chapter provides a methodical analysis of the three categories of market information crucial to B2B marketing: knowledge of customers, knowledge of users, and knowledge of external markets. This research looks at AI through the lens of the conventional data processing framework, analysing the six pillars upon which AI systems are founded. It also explained how the framework’s components work together to transform data into actionable information. In this chapter, the authors will look at how AI works and how it can benefit B2B knowledge-based marketing. It’s not aimed at AI experts but rather at general marketing managers. In this chapter, the possible effects of AI on B2B marketing are discussed using examples from the real world.

This study explores the quality of sustainability reporting (QSR) and the impact of regulatory guidelines, social performance and a standardised reporting framework (using the Global Reporting Initiative [GRI] guidelines) on QSR in the context of banks in Bangladesh.

Using a sample of 315 banking firm-year observations over 13 years (2002–2014), a content analysis technique is used to develop the 11-item QSR index. Regression analysis is used to test the research hypotheses.

Initially, QSR evolved symbolically in Bangladesh's banks but, over our investigation period, with QSR indicators gradually improving, the trends became substantive. The influences on QSR were sustainable banking practice regulatory guidelines, social performance and use of the GRI guidelines. However, until banks improve reporting information, such as external verification and trends over time, QSR cannot be regarded as fully substantive.

This study advances QSR research and debate among academic researchers. With regulatory agencies and stakeholders increasingly using sustainability reporting information for decision making, the information's quality is vital.

This study is the first on QSR in the banking industry context, with previous research mostly investigating the quantity of sustainability reporting. The current study also synthesises QSR with sustainability regulation and social performance factors which have rarely been used in the sustainability literature. To gain a holistic understanding of QSR, existing QSR measures are advanced by combining external reporting efforts with banks' internalisation initiatives.

Big Data can be utilised for efficient use of resources and to provide better services to the resident in order to enhance the delivery of urban services and create sustainable build environment. However, the adoption of Big Data faces many challenges at the implementation level. Therefore, the purpose of this paper is to identify the challenges towards the efficient application of Big Data in smart cities development and analyse the inter-relationships.

The 14 Big Data challenges are identified through the literature review and validated with the expert’s feedback. After that the inter-relationships among the identified challenges are developed using an integrated approach of fuzzy Interpretive Structural Modelling (fuzzy-ISM) and fuzzy Decision-Making Trial and Evaluation Laboratory (fuzzy-DEMATEL).

Evaluation of interrelationships among the challenges suggests that diverse population in smart cities and lack of infrastructure are the significant challenges that impede the integration of Big Data in the development of smart cities.

This study will enable practitioners, policy planners involved in smart city projects in tackling the challenges in an optimised manner for the hindrance free and accelerated development of smart cities.

This research is an initial effort to develop an interpretive structural model of Big Data challenges for smart cities development which gives a clearer picture of how the identified challenges interact with each other.