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Based on the tenets of the conservation of resources (COR) theory, this study investigated the influence of different leadership styles on organizational performance in the context of a Eurasian country (i.e. Kazakhstan). It further examined the moderating role of corporate culture in the leadership-organizational performance relationship.

Using the quantitative survey method, the study collected data from 321 managerial employees working in local and multinational corporations in Kazakhstan. The collected data were analysed using SPSS software, and factor analysis, path analysis and hierarchical regression analysis were conducted to validate the hypotheses. Furthermore, structural equation modelling was developed to assess the moderating effects of the variables.

The findings reveal that among different leadership styles, transformational, transactional and paternal leadership have higher influences on organizational performance. Among different corporate cultures, clan culture appears to have higher moderating effects on the leadership-organizational performance relationship. The moderating role of corporate culture on the leadership influence-organizational performance relationship supports the “resource caravan” effects of the composition model theory.

Based on the premises of the COR theory, this study suggests developing multiple leadership competencies among managerial employees to be more effective in any given organizational or country context. As a result of the inclusiveness of multiple competencies, the study further suggests the consideration of an “integrated leadership approach” in the Eurasian context. Consistent with the national cultural syndrome, and as preferred by employees, managers could focus on developing a clan or group culture to strengthen their influencing power on employees.

The study adopts the COR theory by considering leadership competencies as unique resources of individual managers, which suggests the development of an “integrated leadership approach” for better management development and improved organizational performance. Furthermore, the study contributes by validating the applicability of the “conservation of resources” and the “composition model” theories in leadership studies.

Using a multi-level perspective, the purpose of this paper is to investigate impact of transformational leadership on employees’ creative process engagement and mediating roles of intrinsic motivation, task complexity and innovation support in the process of influence.

This study follows a quantitative method. Using a multi-item survey instrument, a total of 400 questionnaires were distributed among employees of small and medium enterprises registered with the Chittagong Chamber of Commerce and Industry in Bangladesh. Collected data were analyzed using structural equation model as well as factor analysis and path analysis to test the hypotheses and to assess the moderating and mediating effects of the variables.

The findings reveal that transformational leadership has a significant impact on employees’ creative process engagement. The study further shows that task complexity and support for innovation moderate the relationship between transformational leadership and employees’ creative process engagement.

Based on the premises of interactionist perspectives on creativity, this study integrates multi-level variables to investigate leaders’ influences on followers’ creative process engagement. This study contributes to the existing literature by providing empirical evidence on influence of transformational leadership on employees’ creative process engagement as well as the impact of both individual- and organizational-level variables.

The study adopts a distinct model comprising five different variables to investigate creative process engagement from a multi-level perspective, i.e., creative process engagement and intrinsic motivation at the individual level, task complexity at the unit level, and support for innovation and leadership at the organizational level. This integrated model of using predictors from multiple levels supports the theoretical assumptions that creative process engagement results from the interaction of individual-, group- and organizational-level factors.

Adopting a multi-level research approach, this study aims to investigate the impact of employee engagement on team performance. It further explores the mediating effects of employee commitment and organizational citizenship behaviour on the employee engagement–team performance relationship.

The study follows a quantitative method. Data were collected through a self-administered questionnaire survey using snowball and convenience sampling. Descriptive statistics and bi-variate correlation analyses were conducted using SmartPLS 2 and SPSS 20 software, and subsequently, a structural equation model was developed.

The study suggests that better employee engagement could improve team performance in organizational contexts. Organizational commitment and citizenship behaviour played a mediating role in the employee engagement–team performance relationship. Further research on the meditating effects of demographic factors is suggested to advance knowledge in the employee engagement domain.

Based on premises of the social exchange theory and the employee stewardship theory, the study integrates multi-level variables to impact of individual employee engagement on organizational team performance. The findings of the study contribute to the existing literature by providing empirical evidence of the impact of individual-level variables on team-level performance. It reiterates the need for multi-level modelling of organizational behavioural research.

The study used a multi-theoretical approach to investigate team performance in organizational contexts, i.e. individual employee engagement, organizational commitment and organizational citizenship behaviour. This integrated model using predictors from multiple levels demonstrates that team performance could be enhanced from interactions of different factors of individual behaviour.

Given that individual creativity is a critical element to achieving organizational competitiveness, the purpose of this study is to attempt to investigate how transformational leadership (TL) drives employee creative process engagement (CPE) by improving their creative self-efficacy (CSE).

Analysis has been performed based on 194 responses from information and communication technology firms using a cross-sectional survey design. The study follows a deductive research approach to test the hypotheses. It uses SmartPLS2 and IBM SPSS 21 for a structural equation model.

The investigation finds that TL significantly predicts CPE, and CSE partially mediates the TL–CPE relationship. The result demonstrates that TL shapes an organizational climate conducive to the employees’ CPE by building employees’ self-efficacy.

The study sample was drawn from a single sector of the Bangladeshi economy. The sampling design represents a limitation, for which the findings cannot be broadly generalized. Replications and augmentations of the study in various industrial areas will help test the robustness and generalizability of the discoveries.

TL and CPE are desirable organizational outcomes across all cultures. From a practical standpoint, the outcomes demonstrate that TL is linked to CPE and CSE among information and communication technology employees. This study extends the appropriateness of CSE into Asian countries. Notably, it provides additional insight into a contemporary TL model that can unequivocally impact leadership development in the Bangladeshi information and communication technology firms. Managers or chief executive officers in the small and medium enterprises are expected to exhibit TL attributes by designing a supportive organizational climate that will motivate employees to exhibit creative activities.

TL transforms employees’ psychological state to get them to engage in creative processes, benefiting the organizational stakeholders by their unconventional creative behavior. The TL-driven innovative outcome through employees’ CPE contributes to the development of social well-being.

This paper adds significance to the extant literature regarding the determinants of the mediating impact of CSE on TL and CPE from the viewpoints of information and communication technology firms, particularly from developing countries, such as Bangladesh. It also contributes to reconcile the findings of the previous studies around the globe in both developed and developing countries.

The purpose of this paper is to investigate the influence of an employee’s personal creative identity on their innovation behaviour in knowledge-intensive information technology (IT) service provider firms. It further investigates the mediating role of an employee’s creative process engagement (CPE) and the moderating effects of the organizational creative climate on creative identity-innovative behaviour (IB) relationships.

This study follows a quantitative method. Using a multi-item survey instrument, a total of 316 questionnaires were collected from the employees of IT service provider firms in Chittagong, Bangladesh. The collected data were analysed using structural equation modelling, factor analysis and path analysis to test the hypotheses and to assess the moderating and mediating effects of the variables.

The results revealed the significant influence of an employee’s creative personal identity (CPI) on their IB. The mediation analysis revealed that CPE mediates the association between a CPI and IB. The study also found a significant moderating effect of a creative organizational climate between a CPI and CPE.

Based on the premise of the interactionist approach of creativity and role identity theory, this study contributes to the creativity and innovation literature by providing empirical support for the relationship between a personal creative identity, organizational creative culture, CPE and IB in IT service organizations.

This study adopts a distinct model comprising four different variables to investigate an employee’s IB from a multi-level perspective, i.e., a creative identity and CPE at the individual level and a creative climate and IB at the organizational level. This integrated model using predictors from multiple levels supports the theoretical assumption that IB results from the interaction of individual and organizational level factors.

The purpose of this paper is to evaluate the prevalence and antibiograms of bacteria isolated from various fresh fruit juices at a local market in Faisalabad.

Fresh fruit juice samples (n=125) were randomly collected using aseptic technique. Each sample (10 mL) was serially diluted with 90 mL of sterile peptone water, from 1×10⁻¹ to 1×10⁻⁵. Each dilution was then used to inoculate nutrient agar by surface spread plating. Aerobic colony counts (ACCs) were determined by colony counting. The isolates were sub-cultured on blood and MacConkey agar. Preliminary identification was achieved on the basis of colony morphology and culture characteristic, and confirmed by API® 20E, 20NE, and API® Staph testing. Antimicrobial susceptibility testing was carried out using the Kirby-Bauer disk diffusion assay, per CLSI 2015 guidelines.

The mean ACC ranged from 2.0×10⁶ CFU/mL to 4.93×10⁶ CFU/mL, with the highest ACC determined for orange juice. Overall, 153 polymicrobial were identified in 125 samples; 103 of these were Gram-negative rods (GNR) and 28 were Gram-positive cocci (GPC). Escherichia coli (n=38), Klebsiella pneumoniae (n=32) and Pseudomonas aeruginosa (n=24) were the predominant GNR; Staphylococcus aureus (n=28) was the predominant GPC. Antibiogram analysis revealed that all GNR were resistant to ampicillin. However, most E. coli isolates were resistant to ceftazidime (72.4 percent of isolates), and ceftriaxone and cefepime (68.9 percent), while most K. pneumoniae isolates were resistant to cefepime (72 percent) and ceftriaxone (64 percent). All S. aureus isolates were resistant to penicillin, while most (64 percent) were resistant to piperacillin; the most effective drugs against bacteria were vancomycin and imipenem.

The findings suggest that the local government regulatory food and public health authorities should take immediate emergency measures. Appropriate surveillance studies and periodic monitoring of food items should be regularly performed to safeguard public health.

The current study revealed the prevalence of multidrug-resistant bacteria in freshly prepared fruit juices sold by local street vendors.

The purpose of this paper is to test the dynamic linkages among the stock markets of four South Asian countries (India, Pakistan, Bangladesh and Sri Lanka) in the backdrop of trade interdependency.

Listed indices are used to serve the proxy of stock markets of four countries for the period: January 2000–December 2018. The study uses the autoregressive distributed lag model and Granger causality techniques in multivariate frameworks while focusing on intraregional trade as an exogenous factor for testing the long- and short-run causality in the given data set, hence raising the quality of statistical inference.

The results highlight that India and Pakistan are net exporters to the South Asian region, while Bangladesh and Sri Lanka are net importers from the region. While testing the stock markets linkages, the expanded intraregional trade volumes (exports plus imports) have occurred with the significant cointegration of stock markets of India and Pakistan with the other stock markets in the long run. In the short run, the stock markets of India, Pakistan and Sri Lanka report bidirectional causality without having significant spillovers of intraregional trade on the stock prices.

The study relies on the multivariate techniques with stock prices and regional trade share as the exogenous variables. Further the regulatory, political and economic conditions of sample countries are fundamentally different which in turn affect their degree of trade interdependency and integration between the stock markets.

Nonsignificant cointegration of the stock markets of Sri Lanka and Bangladesh highlights the possibility of portfolio diversification in the long run, while the significant bidirectional causalities between the stock markets highlight the lesser degree of portfolio diversifications in the short run.

Pioneer efforts are made to examine the dynamic linkages between the South Asian stock markets while focusing on regional trade interdependency. The results provide new insight in the dynamics of stock returns of South Asian stock markets in the backdrop of intraregional trade.

Corporate social responsibility (CSR) aims at upholding socio-economic condition of deprived communities prevailing in society as well as bringing profitability for corporate companies themselves. This study investigates to what extent the CSR initiatives of financial institutions in Bangladesh have been able to reach out to deprived communities and support various dimensions of financial inclusion (FI) in the country.

In this study, both supply-side and demand-side data are included and discussed rigorously as tools to cross-check the result. Both qualitative and quantitative data are incorporated, and graphs and tables are used to represent the critical information better. A triangulation of in-depth interviews with secondary data is used to ensure rigor and trustworthiness. The triangulation approach works as a method to verify secondary data by interviewees in this study.

The result shows a positive geographical and demographical penetration of CSR activities, but it does not necessarily bring FI in all cases. This study identifies some key issues that prevail in the current context of Bangladesh, such as usage, distance, quality and cost of financial products.

This study makes use of both supply-side and demand-side information and thus explain the reasons behind the involuntary exclusion of financial services.

Purpose – In this article, we examine the nature and the extent of corporate environmental and climate change disclosures in Bangladesh.

Design/methodology/approach – For this purpose, we have undertaken a content analysis of annual reports related to the year 2008 and websites of the 100 largest companies (according to market capitalization) listed on the Dhaka Stock Exchange. We have used 24 content analysis categories to capture the relevant disclosures related to climate change and other environmental issues.

Findings – Key findings of our analysis suggest that the level of environmental and climate change disclosures is very low in Bangladesh. Although 91% of companies made disclosures in at least one category, most companies disclosed information only on the “energy usage” category, which is a mandatory requirement. Even fewer companies made disclosures in the specific areas of climate change. No disclosure was made in the significant categories such as GHG emissions. The second most popular category related to climate change was adaptation measures. Among the other environmental disclosures, a significant finding is that only 5% of (website 6%) companies disclosed that they had an effluent treatment plant. Closer examination of the nature of disclosures suggests that most of the disclosures are positive and descriptive in nature.

Originality/value – As far as we are aware, this is the first study of its kind in Bangladesh which systematically examines corporate climate change disclosures as a particular focus of research.

The goal of the current research is to use different machine learning (ML) approaches to examine and predict customer reviews of food delivery apps (FDAs).

Using Google Play Scraper, data from five food delivery service providers were collected from the Google Play store. Following cleaning the reviews, the filtered texts were classified as having negative, positive, or neutral sentiments, which were then scored using two unsupervised sentiment algorithms (AFINN and Valence Aware Dictionary for sentiment Reasoning (VADER)). Furthermore, the authors employed four ML approaches to categorize each review of FDAs into the respective sentiment class.

According to the study's findings, the majority of customer reviews of FDAs were positive. This research also revealed that, while all of the methods (decision tree, linear support vector machine, random forest classifier and logistic regression) can appropriately classify the reviews into a sentiment category, support vector machines (SVM) beats the others in terms of model accuracy. The authors' study also showed that logistic regression provided the highest recall, F1 score and lowest Root Mean Square Error (RMSE) among the four ML models.

The findings aid FDAs in determining customer review behavior. The study's findings could help food apps developers better understand how customers feel about the developers' products and services. The food apps developer can learn how to use ML techniques to better understand the users' behavior.

The current study uses ML methodologies to investigate and predict consumer attitude regarding FDAs.