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Reverse logistics (RL) is a type of supply chain management that moves goods from the end customer to the original manufacturer for reuse, remanufacturing and disposal purposes. Owing to growing environmental legislations and the development of new technologies in marketing, RL has attracted more significance among experts and academicians. Outsourcing RL practices to third-party reverse logistics provider (3PRLP) has been identified as one of the most important management strategies due to complexity of RL operations and the lack of available resource. Current sustainability trends have made 3PRLP assessment and selection process more complex. In order to select the 3PRLP, the existence of several aspects of sustainability motivates the experts to establish a new multi-criteria decision analysis (MCDA) approach.

With the growing complexity and high uncertainty of decision environments, the preference values of 3PRLPs are not always expressed with real numbers. As the generalized version of fuzzy set, intuitionistic fuzzy set and Fermatean fuzzy set, the theory of q-rung orthopair fuzzy set (q-ROFS) is used to permit decision experts (DEs) to their assessments in a larger space and to better cope with uncertain information. Given that the combined compromise solution (CoCoSo) is an innovative MCDA approach with higher degree of stability and reliability than several existing methods.

To exhibit the potentiality and applicability of the presented framework, a case study of S3PRLPs assessment is taken from q-rung orthopair fuzzy perspective. The assessment process consists of three sustainability aspects namely economic, environment and social dimensions related with a total of 14 criteria. Further, sensitivity and comparative analyses are made to display the solidity and strength of the presented approach. The results of this study approve that the presented methodology is more stable and efficient in comparison with other methods.

Thus, the objective of the study is to develop a hybrid decision-making methodology by combining CoCoSo method and discrimination measure with q-ROFS for selecting an appropriate sustainable 3PRLP (S3PRLP) candidate under uncertain environment. In the proposed method, a novel procedure is proposed to obtain the weights of DEs within q-ROFS context. To calculate the criteria weights, a new formula is presented based on discrimination measure, which provides more realistic weights. In this respect, a new discrimination measure is proposed for q-ROFSs.

The locational disadvantage of a health-care centre often restricts adequate delivery of health-care services in an area. The purpose of this study is to examine the status of primary health-care services in such a geographically disadvantageous area which is confined by forests, tea gardens and undulating topography.

Necessary secondary data of 13 primary health centres and 236 sub-centres has been collected from the Office of the Chief Medical Officer of Health. Based on obtained data, Health-care Infrastructure Index has been prepared which has been validated by an expert panel, and subsequently, the Thiessen Polygon method has been applied through Arc GIS software to show spatial variation of health-care services delivered by different health-care centres.

In the study area, there is wide variation found in the case of physical facilities, caregivers and connectivity of road networks, which altogether affect the overall status of health-care services. Among all the indicators, some health-care centres experience staff shortages for prolonged non-recruitment, inaccessibility and inconsistent patient load in different health centres.

In spite of the unfavourable geographical landscape, health-care centres have to be set up wherever possible. There is a need to make new roads and simultaneously the existing road connectivity should be improved so that patients and caregivers can move quickly whenever required. Existing physical facilities need to be renewed or redeveloped along with increasing the number of doctors and other health-care providers as per the need of people with an adequate and optimum level of services.

The Dissolved Oxygen (DO) level of the rivers is a unique indicator of aquatic health. Decrease of DO values will adversely impact the biotic community sustained by the aquatic ecosystems. We analysed the DO level at six sites of the River Ganges adjacent to the megacity of Kolkata during the COVID-19 induced lockdown period in April 2020 and compared it with data collected from 2015 to 2019 without altering the sampling and monitoring protocols. The normal decreasing trend of DO during the time phase of 2015–2019 suddenly exhibited a sharp spike during the COVID-19 lockdown phase. The DO values hiked significantly during COVID-19 lockdown phase in all the stations with the spatial trend Botanical Garden (6.44 mg/l) > Ramkrishna Ghat (6.32 mg/l) > Shibpur Ghat (6.21 mg/l) > 2nd Hooghly Bridge (6.19 mg/l) > Princep Ghat (6.09 mg/l) > Babughat (5.79 mg/l). The data pattern confirms a straightforward improvement of water quality during the lockdown phase in the context of the DO level, which is congenial for aquatic biodiversity of the River Ganges at the local scale.

The purpose of this paper is to analyze numerically forced convective conjugate heat transfer characteristics for laminar flow through a wavy minichannel.

The mass and momentum conservation equations for the flow of water in the fluidic domain and the coupled energy conservation equations in both the fluid and solid domain are solved numerically using the finite element method. The exteriors of both the walls are subjected to a uniform heat flux.

The results reveal that the theoretical model without consideration of the effect of wall thickness always predicts a lower value of average Nusselt number (Nu¯) as compared to the case of conjugate analysis, although it varies with the thickness as well as material of the wall. For the low amplitude of the wall (α = 0.2), the performance factor (PF) becomes very high for Re in the regime of 5 (⩽) Re (⩽) 15. For any geometrical configurations, conjugate heat transfer analysis predicts higher PF as compared to that of nonconjugate analysis.

The present study finds relevance in several applications, such as solar collectors and heat exchangers used in chemical industries and heating-ventilation and air-conditioning, etc.

To the best of the authors’ knowledge, the analysis of combined influences of the thickness and the material of the wall of the channel together with the geometrical parameters of the channel, namely, amplitude and wavelength on the heat transfer and fluid flow characteristics for flow through wavy minichannel in the laminar regime is reported first time in the literature.

Recent research studies have increasingly suggested leadership as a major antecedent to encourage innovative work behavior among business employees. Empirical studies which investigated the influence of various leadership aspects such as style and ethics on employees' innovative performance and unraveled the mechanism through which leadership exerts its impact on employees' innovative work behavior were restricted. Thus, the purpose of this research was to investigate the relationship between ethical leadership and employees' innovative performance by focusing on the mediating role of two forms of the intellectual capital (IC), i.e. human capital and social capital.

Data for present research were collected through in person administered questionnaire-based survey from the managerial level employees of the targeted sample of the manufacturing firms. Furthermore, due consideration was given while selecting the individuals from R&D departments of these organizations, who were typically involved in knowledge-intensive jobs and where application of intellectual assets was needed.

Ethical leadership was observed as to positively influencing employees' innovative performance. Two forms of IC, i.e. human capital and social capital were observed as playing mediating role in the ethical leadership – employees' innovative performance relationship.

The contemporary research study adds value in the literature of the ethical leadership. The most imperative theoretical contribution of the present research study underlines the psychological process, i.e. IC by which ethical leaders encourage innovative behavior among employees.

The purpose of this paper is to introduce the special issue on state-owned enterprises (SOEs) in the contemporary global business scenario. Against the theoretical background of and the invited themes for the special issue, the paper presents a summary of key findings and practical implications of the accepted papers and suggests future research directions.

The paper is conceptual, which organized through utilitarianism or legitimism; SOEs scenario 1 – hungry fox, hunting bears; SOEs scenario 2 – dancing elephant, flying bears; what do we know and what we wish to explore; what have been examined; what we need to study further; closing note by bears’ well-wishers; and protocol of the special issue.

By deeply looking into emerging economies (China, India), developed economies (Denmark, Italy, Sweden), transition economies (Tunisia) and diverse sectors (public transport, space), coupled with cross-country sample data, the nine accepted papers have discussed several interesting findings and recommended numerous implications for the policymakers and SOEs’ managers. Drawing upon the interdisciplinary literature, empirical and qualitative papers would deepen the understanding of the growth strategies and performance of SOEs, and the application of management theories such as institutional theory, agency theory, social exchange theory, managerial grid theory, incomplete contracts theory and public governance view, among others. The issue also brings a review-cum-citation analysis paper on the impact of privatization on the performance of SOEs.

The papers have made unique contributions to the public economics, new public management, international business and organizational development literature by critically analyzing the burgeoning phenomenon of the changing dynamics and globalization of SOEs.

This study aims to investigate the Big Social Data (BSD) paradigm, which still lacks a clear and shared definition, and causes a lack of clarity and understanding about its beneficial opportunities for practitioners. In the knowledge management (KM) domain, a clear characterization of the BSD paradigm can lead to more effective and efficient KM strategies, processes and systems that leverage a huge amount of structured and unstructured data sources.

The study adopts a systematic literature review (SLR) methodology based on a mixed analysis approach (unsupervised machine learning and human-based) applied to 199 research articles on BSD topics extracted from Scopus and Web of Science. In particular, machine learning processing has been implemented by using topic extraction and hierarchical clustering techniques.

The paper provides a threefold contribution: a conceptualization and a consensual definition of the BSD paradigm through the identification of four key conceptual pillars (i.e. sources, properties, technology and value exploitation); a characterization of the taxonomy of BSD data type that extends previous works on this topic; a research agenda for future research studies on BSD and its applications along with a KM perspective.

The main limits of the research rely on the list of articles considered for the literature review that could be enlarged by considering further sources (in addition to Scopus and Web of Science) and/or further languages (in addition to English) and/or further years (the review considers papers published until 2018). Research implications concern the development of a research agenda organized along with five thematic issues, which can feed future research to deepen the paradigm of BSD and explore linkages with the KM field.

Practical implications concern the usage of the proposed definition of BSD to purposefully design applications and services based on BSD in knowledge-intensive domains to generate value for citizens, individuals, companies and territories.

The original contribution concerns the definition of the big data social paradigm built through an SLR the combines machine learning processing and human-based processing. Moreover, the research agenda deriving from the study contributes to investigate the BSD paradigm in the wider domain of KM.