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There is a growing trend in online shopping in developing and underdeveloped economies. Measuring web retail service quality is vital to enhance and retain online customers for higher profits. As a result, it is essential to understand e-service quality and its relationship with other e-commerce-related variables identified as customer satisfaction, word-of-mouth (WOM), loyalty and repurchase intention. The main objective of this research is to validate the psychometric properties of E-TailQ and ES-Qual scales to measure e-service quality in the context of an emerging economy.

The study was administered by surveying online customers through a convenience sampling approach. The sample data consisted of 329 valid responses. The data were analyzed using confirmatory factor analysis (CFA) and structural equation modeling (SEM).

The results suggest that both the scales are valid, reliable and adequate and confirm the psychometric properties of E-TailQ and ES-Qual scales in an emerging economy context. There is a positive and significant relationship between latent variables (E-TailQ and ES-Qual) and customer outcome variables like satisfaction, loyalty, WOM and repurchase intention. Additionally, the coefficients of the E-TailQ scale have higher values than ES-Qual scales in all dimensions. The perceived quality proved to be a precedent of satisfaction to a lesser extent than other scales' constructs, and it proved to be a superior predictor of WOM for the E-TailQ scale and loyalty for the ES-Qual scale. Overall, when measured by the ES-Qual scale, perceived quality could explain much of the sample's satisfaction, loyalty and repurchase intention compared to E-TailQ.

One of the significant limitations of this study is related to the data collection, as individual responses were collected at one particular point in time. Thus, it is impossible to verify the development of perceived service quality outcomes over a specific time. Another possible limitation is the selection of only two widely used scales, although other options are available in the literature. Finally, developing a new scale to address future challenges might be another alternative.

The results obtained in the study will help managers assess customer satisfaction, the reputation of the business through WOM, and customer intentions for the repurchase that will lead to loyalty by emphasizing e-service quality. It will enable them to design strategies for improving business performance. The developed instrument will assist in identifying the gaps and describing how service quality can achieve higher levels of customer satisfaction.

Several studies in the literature have used E-TailQ and ES-Qual scales to measure e-service quality in developed countries. Only a few studies addressed the validity of these widely used competing scales in an emerging economy like Pakistan. This study addresses the literature gap by addressing the reliability and validity of these scales and assesses the impact of e-commerce-related variables. Besides, the study reveals insights into the literature by addressing multiple dimensions of e-service quality and summarizes a deep understanding of each scale item that affects the perceived quality in a developing economy like Pakistan.

The aim of the current study is to recommend and compare the estimates of finite element model (FEM), analytical model, and artificial neural networks (ANN) model for capturing the LCC of FCSC members. A database comprising 325 FCSC columns was constructed from previous studies to propose FEM and ANN models while the analytical model was proposed based on a database of 712 samples and encasing mechanics of steel tube and FRP wraps. The concrete damage plastic model was used for concrete along with bilinear and linear elastic models for steel tube and FRP wraps, respectively. Analytical and ANN models effectively considered the lateral encasing mechanism of FCSC columns for accurate predictions.

The study aimed to compare the prediction accuracy of finite element (FEM), analytical, and artificial neural network (ANN) models for the load-carrying capacity (LCC) of fiber reinforced polymer (FRP)-encased concrete-filled steel tube (CFST) compression members (FCSC). A database of 325 FCSC columns was developed for FEM and ANN models, while the analytical model was based on 712 samples, utilizing encasing mechanics of steel tube and FRP wraps. FEM used a concrete damage plastic model, bilinear steel tube, and linear elastic FRP models. Statistical accuracy was evaluated using MAE, MAPE, R², RMSE, and a 20-index across all models.

Based on the experimental database, the FEM presented the accuracies in the form of statistical parameters MAE = 223.76, MAPE = 285.32, R² = 0.94, RMSE = 210.43 and a20-index = 0.83. The analytical model showed the statistics of MAE = 427.229, MAPE = 283.649, R2 = 0.8149, RMSE = 275.428 and a20-index = 0.73 while ANN models portrayed the predictions with MAE = 195, MAPE = 229.67, R² = 0.981, RMSE = 174 and a20-index = 0.89 for the LCC of FCSC columns.

Although various investigations have already been performed on the prediction of the load-carrying capacity (LCC) of fiber reinforced polymer (FRP)-encased concrete-filled steel tube (CFST) compression members (FCSC) using small and noisy data, none of them compared the accuracy of prediction of different modeling techniques based on a refined large database.

The external confinement provided by the fiber-reinforced polymer (FRP) sheets leads to an improvement in the axial compressive strength (CS) and strain of reinforced concrete structural members. Many studies have proposed analytical models to predict the axial CS of concrete structural members, but the predictions for the axial compressive strain still need more investigation because the previous strain models are not accurate enough. Moreover, the previous strain models were proposed using small and noisy databases using simple modeling techniques. Therefore, a rigorous approach is needed to propose a more accurate strain model and compare its predictions with the previous models.

The present work has endeavored to propose strain models for FRP-confined concrete members using three different techniques: analytical modeling, artificial neural network (ANN) modeling and finite element analysis (FEA) modeling based on a large database consisting of 570 sample points.

The assessment of the previous models using some statistical parameters revealed that the estimates of the newly recommended models were more accurate than the previous models. The estimates of the new models were validated using the experimental outcomes of compressive members confined with carbon-fiber-reinforced polymer (CFRP) wraps. The nonlinear FEA of the tested samples was performed using ABAQUS, and its estimates were equated with the calculations of the analytical and ANN models. The relative investigation of the estimates solidly substantiates the accuracy and applicability of the recommended analytical, ANN and FEA models for predicting the axial strain of CFRP-confined concrete compression members.

The research introduces innovative methods for understanding FRP confinement in concrete, presenting new models to estimate axial compressive strains. Utilizing a database of 570 experimental samples, the study employs ANNs and regression analysis to develop these models. Existing models for FRP-confined concrete's axial strains are also assessed using this database. Validation involves testing 18 cylindrical specimens confined with CFRP wraps and FE simulations using a concrete-damaged plastic (CDP) model. A comprehensive comparative analysis compares experimental results with estimates from ANNs, analytical and finite element models (FEMs), offering valuable insights and predictive tools for FRP confinement in concrete.

The purpose of this paper is to present a comprehensive model of the relationship between control and sales performance contingent upon the commitment and adaptive selling variables. Specifically, the study tests the mediator effects of adaptive selling and organizational commitment on the effect of managerial control systems on self-assessed performance of the salespeople working in the field of industrial marketing.

In total, 472 firms active in the industrial marketing field for tangible industry products in Turkey were selected for the research. The proposed model that tested posits relationships among management control variables and adaptive selling, organizational commitment and sales performance measures. Management controls are related to sales performance through the mediating effect of adaptive selling and organizational commitment. Management control styles (output as formal and professional as informal) were the independent variables, while changes in organizational commitment and adaptive selling were tested both as mediators and sales performance as dependent variable, consistent with the reciprocal effects model under analysis.

The findings demonstrated that “control” is positively associated with “sales performance” and “commitment” and “adaptive selling” mediate this relationship. Findings indicate that control impacts sales performance through a mediating mechanism that involves adaptive selling and commitment. Taken together, results showed that adaptive selling and commitment played a critical role in sales performance.

This research is the first to empirically analyse the model regarding the relationship between sales performance, control, adaptive selling and commitment variables.

In the modern era, libraries confront significant service challenges. Some challenges are linked to information resource management which includes direct availability of information for immediate decision making. The Internet of Things (IoT) is a recent technological shift that library personnel should be aware of because it has the potential to enhance information resource management. The purpose of the research is to highlight the willingness to adopt IoT technology in libraries.

This study uses a quantitative research design in which a survey of public sector universities in Nanjing, China, is conducted to investigate the determinants of IoT adoption intention in libraries. A total of 389 responses were captured from experienced library personnel. The literature on technology adoption is then used to formulate quantitative theories. For data analysis, partial least squares structural equation modeling using SmartPLS.

The research highlights the various success factors which support the IoT service adoption process. It is concluded that IoT augmented services in academic libraries must be supported through robust management practices and effective utilization of technological resources. Many libraries have made substantial modifications to their structure in terms of technology and design to satisfy the demands of patrons.

This is an empirical paper that looks at IoT adoption intention in libraries using a quantitative approach through surveying library personnel. The library personnel can aid in the understanding of the motivations behind technology adoption in libraries, particularly of IoT services that may bring about advances in the libraries' capability to provide information access services.

This study aims to present a sustainable approach in the natural dyeing of cellulose fabric followed by nanosilver finishing through a green crosslinker of citric acid for potential antibacterial surgical gown fabrication.

The nanosilver finish was reproduced using the chemical reduction method. The fabric dyeing was performed on a lab-scale dyeing machine, whereas silver nano-finishing through a pad-dry-cure approach. Citric acid was used as an eco-friendly crosslinker. The specimens were characterized for antibacterial activity, surface chemical, textile, color properties and finish release trend.

The results demonstrated the successful application of curcumin dye followed by silver nano-finishing. The resultant fabric exhibited appropriate textile, dyeing performance indicators, hydrophobic behavior and sustainable broad-spectrum antibacterial activity.

The prepared nanosilver-finished/curcumin-treated fabric expressed desirable properties for potential applications in the fabrication of surgical gowns.

The authors found no reports on an extensive examination of nanosilver finishing on the color parameters of curcumin-dyed cellulose fabric while retaining its textile and comfort properties for possible surgical gown fabrication.

Knowledge is considered an asset for any organization. To distribute knowledge and expertise among stakeholders of an organization, there is a need to develop knowledge sharing (KS) culture. However, different factors affect KS. This study aims to identify the influence of trustworthiness (trust, ability, benevolence and integrity) and motivation and reward on KS attitudes and intentions of law students.

The objectives of the study were achieved by using a quantitative research design. Law students of the colleges affiliated with Punjab University were the population for the present research. The sampling frame of the study was all law colleges, and data was collected through a convenient sampling technique. Data was collected through personal visits to sampled colleges. Questionnaires were circulated among 330 respondents and two hundred valid responses were collected with a 61% response rate. Descriptive analysis was completed using SPSS and path analysis was measured through SmartPLS. The quality of the measurement model was assessed and then hypotheses were tested.

Findings revealed that there was no impact of trustworthiness (trust, ability, benevolence and integrity) on the KS attitude of students. However, motivation and rewards significantly impacted (ß = 0.590; p > 0.01) the KS attitudes. KS attitude also has a significant impact on KS intentions (ß = 0.560; p > 0.01).

The current study is a valuable addition to the literature by providing the impact of trustworthiness, motivation and reward on law students’ KS intentions and attitudes in developing countries. The present study also provides insights for authorities and decision-makers in making decisions regarding the development of KS among students.

This paper aims to emphasize economic complexity, tourism, information and communication technology (ICT), renewable energy consumption and foreign direct investment (FDI) as the determinants of carbon emissions.

These economies rely on the tourism sector, and Asian countries rank among the top tourism economies worldwide in terms of tourism receipts. This study uses a series of empirical estimators, i.e. cross-sectional augmented auto-regression distributive lag and panel cointegration, to validate the main hypotheses.

The econometric results confirm an inverted U-shaped association between economic complexity and carbon emissions, validating the economic complexity index induced environment Kuznets curve hypothesis for the selected Asian economies.

Finally, the empirical results admit articulating some imperative policy suggestions to attain a sustainable environment on behalf of outcomes.

Furthermore, ICT and renewable energy consumption are environment-friendly indicators, while FDI and the international tourism industry increase environmental pressure in selected countries. In addition, this study also explores the interaction between renewable energy and ICT with FDI and their effects on carbon emissions. Interestingly, both interaction terms positively respond to the environmental correction process.

Because ICT with FDI may not reduce environmental pollution unless the energy used in FDI projects is greener. Moreover, in Asian economies, industrial and other sectors could increase environmental quality via the role of ICT in FDI.

这些经济体依赖旅游业, 就旅游收入而言, 亚洲国家在全球旅游经济体中名列前茅。本研究使用一系列经验估计量, 即 CS-ARDL 和面板协整来验证我们的主要假设。

本文强调经济复杂性、旅游、信息和通信技术 (ICT)、可再生能源消费和外国直接投资 (FDI) 作为碳排放的决定因素

计量经济学结果证实了经济复杂性与碳排放之间的倒 U 型关联, 验证了 ECI 对选定亚洲经济体的环境库兹涅茨曲线 (EKC) 假设。

最后, 实证结果承认阐明了一些必要的政策建议, 以代表结果实现可持续环境。

此外, 信息通信技术和可再生能源消耗是环境友好型指标, 而外国直接投资和国际旅游业增加了选定国家的环境压力。此外, 本研究还探讨了可再生能源和 ICT 与外国直接投资之间的相互作用及其对碳排放的影响。有趣的是, 这两个交互项都对环境校正过程做出了积极响应。

ICT 与 FDI 可能不会减少环境污染, 除非 FDI 项目中的能源使用更环保。此外, 在亚洲经济体中, 工业和其他部门可以通过 ICT 在 FDI 中的作用提高环境质量。

环境库兹涅茨曲线; 外商直接投资;信息和通信技术; 可再生能源;旅游;亚洲主要旅游经济体

文章类型： 研究型论文

The study advances research on the high-performance work system (HPWS) and innovation performance (IP) linkage by empirically analyzing the serial mediation of human resource flexibility (HRF) and knowledge absorptive capacity (KAC). Previous research on the HPWS–IP linkage underscores the presence of a “black box.” Therefore, the present study aims to unravel the underexplored HPWS–IP relationship through HRF and KAC mediation in the context of the hotel industry.

Survey-based time-lagged data were collected from 303 mid-level managers in the hotel industry. Structural equation modeling (SEM) using Smart-PLS 4 was used to test hypothesized relationships.

The results reveal that HPWS has a significant positive direct relationship with innovation performance, human resource flexibility and knowledge absorptive capacity. Further, both human resource flexibility and knowledge absorptive capacity also serially mediate the HPWS–IP linkage.

The results of the study provide useful insights into the hotel industry in Pakistan by offering empirical evidence that building HPWS in the hotel sector can lead to increased human resource flexibility and enhanced knowledge absorptive capacity, ultimately contributing to improved innovation performance.

Notably, human resource flexibility and knowledge absorptive capacity together as dynamic capabilities represent a novel contribution rarely discussed in the literature, particularly their role as serial mediators between HPWS–IP relationships within the hotel industry.

Purpose: This study investigates internal/own shock in the domestic market and three external volatility spillovers from India, the UK, and the USA to the Sri Lanka stock market.

Need for the Study: The external market’s internal/own shocks and volatility spillovers influence portfolio choices in domestic stock market returns. Hence, it is required to investigate the internal shock in the domestic market and the external volatility spillovers from other countries.

Methodology: This study employs a quantitative method using ARMA(1,1)-GARCH(1,1) model. All Share Price Index (ASPI) is the proxy for the Colombo Stock Exchange (CSE) stock return. It uses daily time-series data from 1^st April 2010 to 21^st June 2023.

Findings: The findings revealed that internal/own and external shocks substantially impact the stock price volatility in CSE. Significant volatility clusters and persistence with extended memory in ASPI confirm internal/own shock in the market. Furthermore, CSE receives significant volatility shock from the USA, confirming external shock. This study’s findings highlight the importance of considering internal and external shocks in portfolio decision-making.

Practical Implications: Understanding the influence of internal shocks helps investors manage their portfolios and adapt to market volatility. Recognising significant volatility spillovers from external markets, especially the USA, informs diversification strategies. From a policy standpoint, the study emphasises the need for robust regulations and risk management measures to address shocks in domestic and global markets. This study adds value to the literature by assessing the sources of volatility shocks in the CSE, employing the ARMA-GARCH, a sophisticated econometrics model, to capture stock returns volatility, enhancing understanding of the CSE’s volatility dynamics.