This study investigates the total factor productivity growth (TFPG) of India's organized manufacturing sector over 43 years (1980–2023), comparing pre- and post-liberalization periods. Using a gross output framework with three inputs (material, labour, capital) and a Translog index, the findings reveal negative TFPG in most disaggregated industries during the pre-reform era, a trend that largely persisted after liberalization. However, the sharpness of this negativity declined noticeably, and a positive shift emerged in the post-pandemic period (2016–17 to 2022–23), except in the chemical sector. Overall, aggregate manufacturing TFP showed pessimistic trends post-reforms. Despite this, Indian manufacturing remains vital for national economic growth, particularly outperforming selected countries during the COVID-19 pandemic. The results underscore the need for productivity-focused trade and industrial policies to help firms build competitive advantages and access export markets. This research offers novel insights into the long-standing debate on whether trade liberalization has significantly enhanced industrial performance in India's shifting policy landscape.

Whereas the introduction of toll road services in the Horn of Africa (HoA) region has been celebrated as a crucial initiative for meeting the growing demand for better transport services, improving citizens’ travel efficiency and stimulating economic development, academic research has done little in examining how these emerging services enhance benefits and satisfaction for users. The lack of empirical insights restricts operators’ ability to improve toll road conditions, customer service at plazas, and emergency response services. This study addresses this gap by conducting an empirical survey among 150 randomly selected toll road users in Ethiopia, a core state in the HoA region. Using a three-factor Transportation Service Quality Framework (TRSQ) and Importance-Performance Analysis (IPA), the findings reveal that toll road conditions and safety, and customer service at plaza dimensions measured using multi-item scales significantly determine users’ satisfaction. Although rescue and emergency response factors show an insignificant effect, our Importance-Performance Analysis highlights that management should still give this dimension due attention to enhance user satisfaction. Relevant managerial implications are discussed.

This research introduces a dynamic, real-time and hybrid intelligent fuzzy Multi-Criteria Decision-Making (MCDM) framework for supplier evaluation in the uncertain logistics con-text. The proposed framework is based on fuzzy logic, dynamic entropy weighting, temporal Basic Unit-Interval Monotonic (BUM) aggregation, Dynamic Fuzzy TOPSIS and Adaptive Neuro-Fuzzy Inference System (ANFIS) optimization to enhance the accuracy, robustness and real-time responsiveness of the decision-making process. The framework dynamically changes the importance of each criterion as a result of the logistics conditions; and assigns greater weight to recent operational information through temporal weighting mechanisms. The fuzzy inference modelling is very useful to place the uncertainty and nonlinear decision relationship in control, and the optimization of ANFIS has improved its adaptive learning capability and prediction reliability. The proposed model was implemented and validated in MATLAB and Simulink environments with a dynamic logistics dataset, including the sup-plier evaluation criteria like shipping cost, lead time, reliability, cargo status, fulfillment ef-ficiency, and route risk. The experimental results yielded 97.0% prediction accuracy, a cor-relation coefficient of 0.933 and low prediction error, which indicated good learning capabil-ity and computational stability. In addition, the real-time Simulink implementation proved adaptive decision behavior in changing continuously logistics conditions. The results ob-tained show that the proposed hybrid intelligent framework is an efficient, scalable and reli-able solution for the applications of intelligent supplier selection and real-time logistics deci-sion making.

Bangladesh has experienced continuous progress in the digital landscape, with a significant portion of the population now having access to online services. This rapid expansion has made online shopping more accessible and contributed to its growing popularity. This study aims to examine the consumer perceptions toward online shopping and identify the factors influencing consumer satisfaction in Sylhet city. Data were collected using purposive sampling from 150 respondents through a structured questionnaire. Descriptive statistics were used for demonstrating demographic characteristics of the respondents and to know the consumer perceptions on online shopping. Reliability analysis, factor analysis and multiple regression were employed to identify the significant factors that affect consumer satisfaction. The findings showed that most of the respondents became aware of online shopping through social media, purchased products from online occasionally and mainly used Facebook rather than another social platform. Factor analysis technique suggested that among the five identified factors product & service value is the most important factor affecting overall satisfaction of consumers. Furthermore, multiple regression analysis revealed that all the identified factors had a statistically significant influence on consumer satisfaction. This research finding gives valuable insight to online retailers on what aspect they should focus on to enhance consumer satisfaction.

Employee performance in the public sector is a crucial factor in determining the effectiveness of government services. However, low levels of motivation and non-participatory bureaucratic communication remain obstacles to improving employee performance. This study aims to analyze the influence of leadership style and communication style on employee performance, considering work motivation as a mediating variable. This study uses a quantitative approach with a survey method on 204 employees. Data analysis was conducted using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique using the SmartPLS 3 application. The results of the analysis indicate that leadership style and communication style have a positive and significant effect on employee motivation and performance, both directly and indirectly through motivation as a mediating variable. Motivation is proven to be a key factor that bridges the influence of these two variables on performance. This study reinforces the importance of participatory leadership style and open communication in building motivation and improving the performance of public sector employees. The practical implication is the importance of developing leadership capacity and a more inclusive communication system in government organizations.

Drawing on conservation of resources theory, this study examines how flexible human resource management affects employee deviant innovation. Survey data were collected from 282 employees working in information technology, machinery manufacturing, and biopharmaceutical firms in Shanghai, Hefei, and Zhejiang Province. Both dimensions of flexible human resource management, coordination flexibility and resource flexibility, were positively related to employee deviant innovation. Psychological resilience mediated both relationships. The supervisor-subordinate relationship moderated the link between psychological resilience and deviant innovation: the stronger the relationship, the weaker the positive effect of resilience on deviant innovation. These findings clarify how flexible human resource management shapes deviant innovation, identify the psychological mechanism through which it operates, and specify the relational condition under which that mechanism is strongest.

The survey assessed the strategies that could effectively improve the application of the participative leadership model in CSR infrastructure delivery in the Niger Delta with a quantitative research design approach. Through multi-stage sampling, a total of 125 participants comprising CSR officers, project managers, site supervisors and community liaison representatives, invited from the core Niger Delta states, Akwa Ibom and Bayelsa, responded to structured, cross-sectional questionnaires as a survey instrument. Data were descriptively analysed using frequency and percentage, while inferential statistics used the Kruskal-Wallis H test. The survey findings indicate 'Relevant training on adoption and implementation of a participative approach', 'Establishment of an organised community project office and non-permanent advisory committees', and 'Allocation of resources for participative engagement and commitment' as key strategies to enhancing the effective application of a participative approach to CSR infrastructure delivery. These strategic variables for fulfilling corporate responsibility are also a panacea for the effective application of the participative model. The study concludes that entrenching these variables would curb the current fragmented application of the model. Additionally, it would strengthen participative engagement and move CSR delivery from mere passive consultation to active partnership for sustainable regional progress and stability, fostering mutual trust and improving corporate-community relationships.

There are many studies made to explain the relationship between the organizational factors. Burden of them, tried to mathematically model this relationship using traditional methods like PLS (Partial Least Squares), SEM (Structural Equation Modeling), RA (Regression Analysis) or Co-relation analysis. Besides, the limited explanatory variables were recently applied in such studies. Additionally, there are very rare quantitative investigations discovering the structural cause and effect interconnections among the huge number of organizational factors. This research has been designed to first distinguish the cause and effect group among the 20 organizational factors and second to weight these factors as well. DEMATEL and SWARA methodologies are the main multi criteria tools used in the present study. Results show the top 4 factors of EBLPOC(Employees' Basic Level of Perception Regarding Organizational Complexities), OCB(Organizational Citizenship Behavior), BC(Business Climate) and EJP(Employee Job Performance) hold relatively the utmost weights (closely 0.826 together). EBLPOC, EJP and BC are the cause factors. OCB is recognized as the effect factor. Furthermore, it is worthy to mention that the factor of EBLPOC (as a qualitative variable which were usually missed or ignored in previous studies), is totally ranked at first position. Finally, present study is inherently readdressing the organization's leaders, chief executives, intermediate managers and policy makers to focus on some classical foremost factors like OCB, BC and EJP (the old wounds) again.

The study aims to analyze trends in the number of leading Angolan insurance companies for benchmarking purposes in the sector between 2020 and 2023, using the DEA-VRS window model. The analysis was conducted by calculating the efficiency scores of each insurer in two-year-wide moving windows, followed by a comparison of efficiency distributions over time and the identification of the insurers that served as benchmarks in each window for benchmarking purposes. The analysis was conducted by calculating the efficiency scores of each insurer in two-year movable windows, followed by a comparison of efficiency distributions over time and the identification of the insurers that served as benchmarks in each window for benchmarking purposes. The results reveal a trend of increasing average efficiency scores and a concomitant reduction in the number of insurers identified as benchmarks, a pattern that was consistently evident across the three analysis windows. In practical terms, the findings also indicate that the universe of benchmarks is becoming more concentrated, which requires attention to the periodic updating of the analysis windows and the selection of variables to ensure that benchmarking continues to reflect efficient practices within the analyzed sample. The article stands out for exploring a little-studied market, using robust primary data, offering practical value by identifying benchmark insurers, and revealing an unexpected inverse relationship between average efficiency and the number of benchmarks DMUs.

Despite 72 percent of organizations adopting artificial intelligence, nearly half of implementations fail due to employee resistance, a paradox that challenges technology acceptance models. Prior research has examined either cognitive acceptance or motivational responses in isolation, leaving the interplay between these pathways and their ethical contingencies unresolved. This research addresses this critical gap through a sequential explanatory mixed-method design combining a quantitative survey of 1,785 employees in AI-adopting organizations with in-depth qualitative interviews with 19 participants, analysed using SmartPLS 4 for structural equation modelling and NVivo 14 for thematic analysis. The findings reveal three key insights. First, psychological empowerment mediates the relationship between technology characteristics and job satisfaction more strongly than technology acceptance, a counterintuitive finding that challenges the technology acceptance model's 30-year dominance. Second, job satisfaction emerges as the strongest predictor of organizational performance. Third, ethical leadership moderates both pathways, such that high ethical leadership amplifies empowerment effects by 34 percent. This research advances a novel Ethical Dual-Pathway Technology Acceptance Model (EDP-TAM), offering actionable guidance for organizations to implement AI that simultaneously optimises performance and safeguards employee well-being.