Search results

The purpose of this study is to examine the determinants impacting consumer behaviour in organic food consumption in Bangladesh. This study aims to identify the key factors facilitating organic food consumption and establish a framework by analysing their contextual relationships.

The study used interpretive structural modelling (ISM), relying on expert perspectives from experienced academicians and marketing professionals. A Matrice d'Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) analysis was performed to assess the driving forces and interdependencies among these determinants.

The MICMAC analysis grouped determinants influencing organic food purchases into four categories. The dependent factors, like attitude and food safety, showed moderate driving forces and high dependence. Linkage determinants, such as environmental concern and price, exerted considerable influence with moderate dependence. Independent variables, especially knowledge about organic food, had a strong impact with relatively low dependence.

This study’s insights offer valuable guidance for managers in the organic food industry, providing strategies to address consumer behaviour. Prioritising education on environmental benefits, transparent pricing, collaborating on policies, ensuring food safety and understanding determinants impacting purchase intent can aid in designing effective marketing strategies and product offerings aligned with consumer needs, ultimately promoting sustainability.

To the best of the authors’ knowledge, this study is the first to investigate the interconnections and relative significance of determinants influencing organic food purchases, using the ISM approach and MICMAC analysis. It delves into the previously unexplored territory of understanding the relationships and hierarchical significance of these determinants in shaping consumer behaviour towards organic food purchases.

This study aims to investigate the importance and effect of asymmetric technological collaborations’ key success factors in developing countries. The number of collaborations between large enterprises and SMEs, known as asymmetric technological collaborations (ATC) is growing considerably. But this asymmetry in itself can increase the number and intensity of collaboration challenges. So far, limited studies have been conducted on the stability of ATCs, and most of them have been in the context of developed countries. Meanwhile, studying the strength and stability of collaboration in the nano industry with growing market value and increasing newcomers is of particular importance.

Here, with bionic engineering approach, we used chemistry for the first time to identify the main stability factors of ATCs and build our hypotheses and research model. To this end, we introduced the factors affecting the stability of the dative chemical bond as a bionic counterpart of corporate venture capital (CVC), which is a type of ATC, and proposed 4 hypotheses. We used structural equation modeling (SEM) with partial least squares (PLS) method to examine the hypothesized relationships.

The analysis of survey questionnaire data from 26 asymmetric collaborations in Iran’s nanotechnology industry shows that “learning of the acceptor company” with a negative effect, “network ties” and “development of the collaboration host region” with a positive effect and “diversity in the collaboration portfolio” with an inverted U-shaped effect are the most influential factors in the stability and continuity of CVCs, respectively.

The findings of this research can be the beginning of a broad path leading to exploring and getting inspiration from chemistry to analyze management issues.

The study aimed to assess the digital literacy skills of the students of Sacred Heart College, Chalakudy, to know whether they possess the digital literacy skills to perform well in the digital environment. The study also analyzed how digital literacy skills were affected by various factors.

The study used stratified random sampling technique, and data were collected through a self-assessment survey using an online questionnaire designed based on DigComp 2.1: The Digital Competence Framework by the European Commission.

The results indicated that the college students needed training on digital literacy skills, as the majority students had only moderate to low digital literacy skills. It was proven that exposure to technology and the Internet will not necessarily yield skills to perform well in the digital environment. Also, digital literacy skills were not affected by various factors like age, level of study, etc.

The study helped to identify the digital literacy deficiencies in the students of Sacred Heart College, and it can serve as a valuable model for conducting similar investigations in diverse educational institutions. Conducting such studies offers institutions valuable insights, enabling them to create and implement personalized digital literacy training programs that can enhance students' abilities to navigate the digital landscape with proficiency and effectiveness. The study results can be insightful for educators, policymakers and the Kerala Government to reassess the current approaches and design an effective curriculum for integrating technology in education.

Although there are several studies that evaluated college students’ digital literacy in India and other countries, there are very few studies in the context of Kerala. Therefore, this study is distinctive and will serve as an example for all such studies in the future.

This paper aims to examine and compare extant literature on the application of multi-criteria decision-making (MCDM) techniques in humanitarian operations (HOs) and humanitarian supply chains (HSCs). It identifies the status of existing research in the field and suggests a roadmap for academicians to undertake further research in HOs and HSCs using MCDM techniques.

The paper systematically reviews the research on MCDM applications in HO and HSC domains from 2011 to 2022, as the field gained traction post-2004 Indian Ocean Tsunami phenomena. In the first step, an exhaustive search for journal articles is conducted using 48 keyword searches. To ensure quality, only those articles published in journals featuring in the first quartile of the Scimago Journal Ranking were selected. A total of 103 peer-reviewed articles were selected for the review and then segregated into different categories for analysis.

The paper highlights insufficient high-quality research in HOs that utilizes MCDM methods. It proposes a roadmap for scholars to enhance the research outcomes by advocating adopting mixed methods. The analysis of various studies revealed a notable absence of contextual reference. A contextual mind map specific to HOs has been developed to assist future research endeavors. This resource can guide researchers in determining the appropriate contextual framework for their studies.

This paper will help practitioners understand the research carried out in the field. The aspiring researchers will identify the gap in the extant research and work on future research directions.

To the best of the authors’ knowledge, this is the first literature review on applying MCDM in HOs and HSCs. It summarises the current status and proposes future research directions.

This study aims to investigate earnings management practice of classification shifting of revenues in Chinese-listed firms.

The study employs a dataset of 2,920 A-listed firms from Chinese stock exchanges of Shanghai and Shenzhen for the period of 2003–2019. We apply both univariate and panel regression analysis by using fixed effect estimation with robust standard errors.

Our findings reveal that firms misclassify revenues by taking advantage of the flexibility provided by applicable financial reporting standards. The empirical evidence obtained through regression analysis suggest that managers reclassify non-operating revenues as operating revenue to alter the economic reality while seeking the advantage of financial reports users’ vulnerability for valuing the upper half of income statement items more as compared to lower part. The results further indicate that international financial reporting standards adoption inhibits the earnings management practices using classification shifting of revenues. It is also concluded that firms, which are suffering losses or having low growth, are more persistently involved in misclassification of revenues.

The study is unique from the point of view that it investigates earnings management from the prospective of revenue’s classification in an emerging market characterized by various market imperfections such as lower investor protection and higher information asymmetry.

Policymakers are developing national strategic plans to encourage organizations to adopt Construction 4.0 technologies. However, organizations often adopt the recommended technologies without aligning with organizational vision. Furthermore, there is no prioritization on which Construction 4.0 technology should be adopted, including the impact of the technologies on different criteria such as safety and health. Therefore, this study aims to evaluate Construction 4.0 technologies listed in a national strategic plan that targets the enhancement of safety and health.

A list of Construction 4.0 technologies from a national strategic plan is evaluated using the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method. Then, the data are analyzed using reliability, fuzzy TOPSIS, normalization, Pareto, sensitivity, ranking and correlation analyses.

The analyses identified six Construction 4.0 technologies that are critical in enhancing safety and health: Internet of Things, autonomous construction, big data and predictive analytics, artificial Intelligence, building information modeling and augmented reality and virtualization. In addition, six pairs of Construction 4.0 technologies illustrate strong relationships.

This study contributes to the existing body of knowledge by ranking a list of Construction 4.0 technologies in a national strategic plan that targets the enhancement of safety and health. Decision-makers can use the study findings to prioritize the technologies during the adoption process. Also, to the best of the authors’ knowledge, this study is the first to evaluate the impact of Construction 4.0 technologies listed in a national strategic plan on a specific criterion.

A shared set of moral standards, ethical principles and behavioral norms of social structure can be referred to as culture. Many health problems are strongly influenced by one’s cultural background. The purpose of the paper is to examine the scientific explanation of indigenous norms and practice of health healing.

This qualitative study considered in-person interviews to know the Tribals’ indigenous healing practice in Bangladesh. A focus group discussion with five tribal students was conducted to form a baseline on Tribals’ norms, rituals and information-sharing behavior. Around 35 tribal students were interviewed to find out their healing practices, norms and rituals on health issues. All these practicing indigenous knowledge were documented instantly. Peer-reviewed scientific papers from renowned databases were searched to have scientific evidence on each case. All the studies having negative or positive evidence were mentioned with each case.

The findings showed more indigenous knowledge with scientific disagreements on health aspects among the Tribals’ health practice in Bangladesh. However, the positive impact of such knowledge is not negligible. Therefore, showcasing the scientific tribals’ indigenous knowledge to a global audience is a strong recommendation.

Health and health care-seeking behavior among the tribal population in Bangladesh is not a new area of research, few studies have focused on the context, reasons and choices in patterns of health care-seeking behavior; obstacles and challenges faced in accessing health-care provision in the tribal areas in the country. However, research attempts to show the relationship between ecological knowledge and scientific indication is new in nature.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.

The purpose of this study is to see if market timing predicts the first reporting of earnings performance after the issue, i.e. the issue-year earnings performance. Furthermore, this study examines the behaviour of financial and non-financial issuers’ performance in the light of varied market timings.

This study focuses on 785 NSE-listed initial public offerings that took place between April 2010 and December 2021. This study evaluates market timing by using moving averages. Using multiple regression analysis, the research further investigates the impact of market timing on issue-year earnings performance for financial and non-financial issuers on the basis of an interaction (moderation) effect.

This study finds that there is a significant presence of market timing in India, which predicts issue-year earnings performance. This study also demonstrates that hot market issuers’ performance is heavily influenced by market timing for non-financial issuers only. However, financial companies are not influenced by market timing.

The findings of this study will assist the potential investors, analysts and stakeholders about performance of public issuers in India. Lower earnings performance for hot market non-financial issuers implies that the issuers’ market performance may not be supported by earnings figures. A market performance that is not synchronous with earnings will not last long. The findings of this study hold implications to the regulators as well to keep an eye on issuers’ earnings performance alongside the stock performance. Apart from that, the observations in context of financial and non-financial issuers provide insight about the variation in performance of public issues on the basis of background.

To the best of the authors’ knowledge, this is the only study to examine earnings performance in the context of market timing in India. This study holds significance in terms of methodology for anticipating the presence of market timing and the study of interaction effects. Moreover, it is one of the few studies that has focused on comparing financial and non-financial issuers around the world.

Employee work engagement has become a major concern for managers as hardly 21% of employees are engaged in their work. Therefore, this study aims to unveil the association between ethical leadership and employee engagement. Specifically, the study explores the mediating role of trust in leader between ethical leadership and employee work engagement and moderating role of harmonious work passion in the association between trust in leader and employee work engagement.

This study collected data from 491 employees and their immediate supervisors working in various organizations (in Pakistan) through “Google Forms”. The data were analyzed through analysis of moment structure (AMOS) and structural equation modeling (SEM) was applied to examine measurement model (for unidimensionality) and structural model (for hypotheses testing).

The study noted that ethical leaders positively influence their subordinates to engage in their work. In addition, employees' trust in leader was noted to mediate the association between ethical leadership and employee work engagement. Finally, employees high in harmonious work passion are more likely to engage in their work when perceived their leaders ethical style.

The study suggests to management that fair dealing and involvement in decision-making (ethical leadership) improve employee work engagement as such practices build employees' level of trust in their leaders. In addition, management is suggested to give freedom to employees while selecting their tasks as it positively contributes to their harmonious work passion which ultimately benefits the organization.

Drawing upon social exchange and self-determination theory, this study is the first of its kind that explored the moderating role of harmonious work passion and mediating role of trust in leader between ethical leadership and employee work engagement.