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The purpose of this paper is to enrich the knowledge about blockchain (BC) technology implementation in the agri-food industry by providing an interpretive framework of the key marketing opportunities and challenges, related to the adoption of BC for Geographical Indication (GI) products.

The study adopts an explorative qualitative research design through the cognitive mapping technique applied to the cognition of different market players involved in agri-food BC projects: farmers, distributors, companies and consultancies.

This study presents a comprehensive examination of the marketing impacts of BC across various marketing objectives, including product enhancement, brand positioning, consumer relationships, market access and supply chain relationships. It highlights the capability of BC to facilitate data-enabled ecosystems within the agri-food sector, involving supply chain actors and control agencies. Additionally, the study sheds light on the challenges (technological, collaborative, political, financial and organizational) associated with the implementation of BC in the marketing of agri-food products.

This work provides a comprehensive examination of the relevance of BC in the marketing activities of firms, particularly in the context of quality food products. It highlights the main areas of impact and effects and emphasizes the complexity of the phenomenon, which extends beyond its technical issues. Furthermore, it offers a systematic exploration of the challenges associated with the adoption of BC in marketing activities, thus contributing to a broader understanding of the implications of BC adoption in companies' marketing strategies.

The practical implications for this work addresses both GI companies and policy makers. Implications for companies relate to the market benefits associated with the implementation of BC, which allow further strengthening of market positioning, relationships of trust within the supply chain and integration between physical and digital market channels. The study also systematizes the challenges underlying the implementation of BC projects. The implications for policy makers regard the role they have to play in BC projects at regulatory, financial and policy levels.

Studies focusing on BC applications in marketing are still limited and characterized by a very narrow perspective (especially in the food industry). This study contributes to the conceptual design of the marketing applications of BC in the agri-food sector. The value of the study also lies in having framed the marketing impacts of BC in a holistic perspective, along with the technological and non-technological challenges that are related to the integration of BC in marketing strategy and operations.

Traditionally, life cycle assessment (LCA) has focused on environmental aspects, but integrating social aspects in LCA has gained traction among scholars and practitioners. This study aims to review key social life cycle assessment (SLCA) themes, namely, drivers and barriers of SLCA implementation, methodology and measurement metrics, classification of initiatives to improve SLCA and customer perspectives in SLCA.

A total of 148 scientific papers extracted from the Web of Science database were used and analyzed using bibliometric and content analysis.

The findings suggest that the existing research ignores several aspects of SCLA, which impedes positive growth in topical scholarship, and the study proposes a classification of SLCA research paths to enrich future research. This study contributes positively to SLCA by further developing this area, and as such, this research is a primer to gain deeper knowledge about the state-of-the-art in SLCA as well as to foresee its future scope and challenges.

The study provides an up-to-date review of extant research pertaining to SLCA.

This paper aims to investigate the literacy corpus regarding the potential of big data to improve public decision-making processes and direct these processes toward the creation of public value. This paper presents a map of current knowledge in a sample of selected articles and explores the intersecting points between data from the private sector and the public dimension in relation to benefits for society.

A bibliometric analysis was performed to provide a retrospective review of published content in the past decade in the field of big data for the public interest. This paper describes citation patterns, key topics and publication trends.

The findings indicate a propensity in the current literature to deal with the issue of data value creation in the private dimension (data as input to improve business performance or customer relations). Research on data for the public good has so far been underestimated. Evidence shows that big data value creation is closely associated with a collective process in which multiple levels of interaction and data sharing develop between both private and public actors in data ecosystems that pose new challenges for accountability and legitimation processes.

The bibliometric method focuses on academic papers. This paper does not include conference proceedings, books or book chapters. Consequently, a part of the existing literature was excluded from the investigation and further empirical research is required to validate some of the proposed theoretical assumptions.

Although this paper presents the main contents of previous studies, it highlights the need to systematize data-driven private practices for public purposes. This paper offers insights to better understand these processes from a public management perspective.

Nature’s evolution has shaped intelligent behaviors in creatures like insects and birds, inspiring the field of Swarm Intelligence. Researchers have developed bio-inspired algorithms to address complex optimization problems efficiently. These algorithms strike a balance between computational efficiency and solution optimality, attracting significant attention across domains.

Bio-inspired optimization techniques for feature engineering and its applications are systematically reviewed with chief objective of assessing statistical influence and significance of “Bio-inspired optimization”-based computational models by referring to vast research literature published between year 2015 and 2022.

The Scopus and Web of Science databases were explored for review with focus on parameters such as country-wise publications, keyword occurrences and citations per year. Springer and IEEE emerge as the most creative publishers, with indicative prominent and superior journals, namely, PLoS ONE, Neural Computing and Applications, Lecture Notes in Computer Science and IEEE Transactions. The “National Natural Science Foundation” of China and the “Ministry of Electronics and Information Technology” of India lead in funding projects in this area. China, India and Germany stand out as leaders in publications related to bio-inspired algorithms for feature engineering research.

The review findings integrate various bio-inspired algorithm selection techniques over a diverse spectrum of optimization techniques. Anti colony optimization contributes to decentralized and cooperative search strategies, bee colony optimization (BCO) improves collaborative decision-making, particle swarm optimization leads to exploration-exploitation balance and bio-inspired algorithms offer a range of nature-inspired heuristics.

This study aims to map the conceptual structure and evolution of the recent scientific literature published in marketing journals to identify the areas of interest and potential future research directions.

The 100 most influential marketing academic papers published between 2018 and 2022 were identified and scrutinized through a bibliometric analysis.

The findings further upheld the critical role of emerging technologies such as Blockchain in marketing and identified artificial intelligence and live streaming as emerging trends, reinforcing the importance of data-driven marketing in the discipline.

The data collection included only the 100 most cited documents between 2018 and 2022, and data were limited only to Scopus database and restrained to the Scopus-indexed marketing journals. Moreover, documents were selected based on the number of citations. Nevertheless, the data set may still provide significant insight into the marketing field.

Influential authors, papers and journals identified in this study will facilitate future literature searches and scientific dissemination in the field. This study makes an essential contribution to the marketing literature by identifying hot topics and suggesting future research themes. Also, the important role of emerging technologies and the shift of marketing toward a more data-driven approach will have significant practical implications for marketers.

To the best of the authors’ knowledge, this is the first comprehensive study offering a general overview of the leading trends and researchers in marketing state-of-the-art research.

This research investigates the critical role of data governance (DG) in shaping a data-driven culture (DDC) within organizations, recognizing the transformative potential of data utilization for efficiency, opportunities, and productivity. The study delves into the influence of DG on DDC, emphasizing the mediating effect of data literacy (DL).

The study empirically assesses 125 experienced managers in Indonesian public service sector organizations using a quantitative approach. Structural Equation Modeling (SEM) analysis was chosen to examine the impact of DG on DDC and the mediating effects of DL on this relationship.

The findings highlight that both DG and DL serve as antecedents to DDC, with DL identified as a crucial mediator, explaining a significant portion of the effects between DG and DDC.

Beyond unveiling these relationships, the study discusses practical implications for organizational leaders and managers, emphasizing the need for effective policies and strategies in data-driven decision-making.

This research fills an important research gap by introducing an original model and providing empirical evidence on the dynamic interplay between DG, DL, and DDC, contributing to the evolving landscape of data-driven organizational cultures.

This study focusses on the intersection of social sustainability and human resource management (HRM) as a strategy for crisis management. It aims to provide detailed insight by exploring the associations between socially sustainable HRM (SSHRM), employee well-being, trust in social capital and employee resilience.

This study used a cross-sectional research design to test relationships amongst variables. Data was gathered from employees in India’s private-sector information technology (IT) industry, making the framework relevant to this specific context. The study employed the partial least squares structural equation modelling (PLS-SEM) to analyse complex relationships between the variables.

The results indicate that organisations can boost employee resilience through SSHRM implementation, promote personal well-being (PWB) and family well-being (FWB) and foster trust in social capital. Additionally, the study highlights the moderating impact of employee empowerment, improving the translation of positive employee behaviour in organisational settings.

Our research emphasises the importance of sustainability efforts and strategies focused on social capital to build long-lasting employee connections. This highlights the necessity of incorporating social sustainability objectives into the organisation’s strategic blueprint, ensuring integration into decision-making procedures.

This study uniquely explores the underlying mechanisms through which SSHRM influences employee resilience. An in-depth empirical analysis evinces the causal mechanism between SSHRM, employee well-being, social capital trust and employee resilience.

The purpose of this paper is to empirically investigate the impact of organizational intellectual capital (IC) components on absorptive capacity (ACAP) such as potential absorptive capacity (PACAP) and realized absorptive capacity (RACAP). Furthermore, it attempts to investigate the mechanism through which PACAP and RACAP jointly influence innovation strategies (i.e.) exploitative and exploratory innovations.

This is an explanatory research using a deductive approach. This study uses survey data from 184 manufacturing export firms analyzed through partial least squares structural equation modelling.

The results have found that the cognitive and social capital of a firm positively affects PACAP and RACAP, whereas relational capital has a significant effect on RACAP. Moreover, the study reveals that both potential and realized absorptive capacities considerably lead to the development of organizational exploitative and exploratory innovation strategies.

The research focused on two driving factors, i.e. IC components and ACAP dimensions, and overlooked how each component of IC and ACAP influences ambidextrous innovative strategy.

Providing managers with insights about the critical role of developing IC to facilitate the transfer and exchange of crucial absorptive capacity necessary for ambidextrous innovative strategy.

This study makes a significant contribution to the existing literature by highlighting the importance of ACAP and provides useful insights for firms in developing economies to improve their exploitative and exploratory innovation capability. This study likewise reveals the significance of the four dimensions of IC, which can facilitate bringing in knowledge from developing economies.

Supply chain vulnerability (SCV) analysis is vital for manufacturers globally because it creates a pathway for building resilient supply chains in uncertain environments. This study aims to identify drivers of SCV in the Indian manufacturing sector.

Sixteen drivers were identified from the literature review and followed by expert interviews. Interpretive structural modeling was used to determine the hierarchical structural relationship among identified SCV factors.

It was found that risk is not a board room agenda. Misaligned performance measures with incentives and lack of risk dashboard are the causal factors of SCV. Supply chain security, centralized production and distribution and lack of trust in the supply chain were driven factors.

This provides new insights to assess and prioritize initiatives for supply chain sustainability in terms of continuing business operations. The structural model provides a systemic view of SCV and helps reduce vulnerability.

This study aims to assess the impact of participation in self-help group (SHG) on the psychological empowerment of rural tribal women.

Primary data was collected using multistage random sampling from the rural women of Jharkhand, India. The propensity score matching method was adopted using the psmatch2 command in STATA.

The results show a significant positive change in women’s self-esteem, self-confidence, self-efficacy, autonomy, knowledge and skills, reduction in agony and quality of life after participation in SHG. This reveals that participation in SHG has a significant positive impact on the psychological empowerment of rural tribal women.

Despite the numerous studies on rural women’s empowerment, there is little evidence of literature focusing on the impact of participation in SHG on psychological empowerment, specifically in the tribal context. This study primarily focuses on women belonging to the scheduled tribe category of Jharkhand, one of the poorest states of India.