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E-commerce expands product and service reach, emphasizing the need for strategic market approaches to enhance e-service quality and drive sales growth. This paper aims to assess the relationship between the perceived quality of e-commerce platforms (characterized by measures of order and return convenience), customer satisfaction with online shopping and repurchase intention from online stores as well as examine whether demographic variables such as age, gender and area of residency (urban/rural) influence the ratings of each of these variables.

An online, self-administered survey gathered 108 valid responses from e-commerce customers. Data were analyzed in Statistical Package for the Social Sciences (SPSS) and Analysis of Moment Structures (AMOS) through principal component analysis, confirmatory factor analysis and structural equation modeling (SEM) as well as correlation, descriptive statistics, difference of means tests and nonlinear regression.

Online shopping on e-commerce platforms is seen as convenient for both placing orders and managing returns. Additionally, consumers express satisfaction with their online shopping experiences and exhibit a strong intention to repurchase. The analysis revealed linear relationships between order convenience and customer satisfaction, between order convenience and repurchase intention and nonlinear relationships between return convenience, customer satisfaction and repurchase intention. No significant difference was found between the way the demographic variables rated the convenience, satisfaction and repurchase intention constructs.

This study contributes to the empirical literature on service quality in e-commerce by providing a streamlined model of the interactions among the factors as well as by isolating the nonlinear relationships and comparing results across three demographic variables. From a managerial standpoint, the findings suggest that strategies aimed at providing complete qualitative information and enhancing order and return convenience improve customer satisfaction and foster repurchase intention.

The contemporary business environment is characterised by an increasing reliance on artificial intelligence, automation, optimisation, efficient communication and data-driven decision making. Based on the limited academic literature that examines the managerial perspective on enterprise chatbots, the paper aims to explore organisational needs and expectations for enterprise chatbots from a managerial perspective, assesses the relationship between managerial knowledge and managerial opinion regarding enterprise chatbots, and delivers a framework for integrating chatbots into the digital workforce.

The paper presents a quantitative design. An online, self-administered survey yielded 111 valid responses from managers in service and manufacturing organisations based on convenience and snowball sampling strategies. Given the nature of the data and the research questions, the research was conducted using principal component analysis, parallel analysis, correlation, internal consistency and difference in means tests.

This research explores the managerial perspective on enterprise chatbots from multiple perspectives (i.e., adoption, suitability, development requirements, benefits, barriers, performance and implications), presents a heat map of the average level of chatbot need across industries and business units, highlights the urgent need for education and training initiatives targeted at decision makers, and provides a strategic framework for successful chatbot implementation.

This study equips managers and practitioners dealing with enterprise chatbots with knowledge to effectively leverage the expected benefits of investing in this technology for their organisations. It offers direction for developers in designing chatbots that align with organisational expectations, capabilities and skills.

Insights for managers, researchers and chatbot developers are provided. The work complements the few academic studies that examine enterprise chatbots from a managerial perspective and enriches related commercial studies with more rigourous statistical analysis. The paper contributes to the ongoing discourse on decision-making in the context of technology development, integration and education.

The purpose of this paper is to analyse the influences of different types of knowledge and their inherent dynamics on the effectiveness of the decision-making (DM) process. Knowledge dynamics (KD) is envisioned through the lens of the knowledge fields theory while effective DM process is objectivised via organisational appreciation and reward, higher business performance, sustainable partnerships and managerial satisfaction with previous achievements.

A questionnaire-based survey was conducted with 275 middle managers from companies operating in the business consulting field. The conceptual and structural model was tested using the partial least squares structural equation modelling technique.

The study advances novel insights into the significant positive influences of various knowledge fields on KD on the DM process within real-life business environments. Even though rational knowledge exerts a noteworthy effect on DM, its influence is exceeded by the KD, which proves that integrating emotional and spiritual knowledge in the decisional equation may become a pivotal input to making good managerial decisions regardless of the level of regulation and standardisation in the field.

The research relied on threefold knowledge fields as predictors for the DM process, thus providing a starting point for the development of more complex models.

The study emerges as a groundbreaking approach via the integration and application of the knowledge fields theory within a more comprehensive and empirical outlook on the DM process. Simultaneously, it places DM beyond the unidimensional outcomes of rationality and intuition by urging its intricate and interactional nature.