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Switching behavior is predominantly seen in the consumer buying behavior of the mobile industry. This research aims to identify the factors influencing consumers to switch from their present mobile service provider. The consumer of the mobile industry operates in a dynamic and ever-changing environment that is difficult to predict, so this paper aims to focus on these issues.

The selection of factors was made with the help of qualitative study and quantitative research methods for further findings; with the help of a structured questionnaire, a total of 514 valuable responses were collected to get the results. Exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used to analyze the data.

The finding shows that technology and edge-on-competition (TEC) and pricing have a negative influence on customer switching behavior. The switching cost (SC) is the most significant factor and has a positive impact, while service encounter failure (SEF) also positively impacts switching behavior.

The findings provide important implications for consumers switching brands if they are finding alternative offers that are cost-effective and SEF from service providers

The study of one of the largest mobile markets is learning lessons for other markets around the world. This study will be helpful for mobile service provider companies in their branding and marketing strategies. This study will also be helpful to practitioners, educators and researchers in understanding the consumer behavior of mobile users.

The learning of the largest mobile market will be a great learning lesson for other mobile markets around the world. Consumer behavior will help marketers follow ethical practices and make their strategy so a consumer does not switch brands and remain satisfied with the existing brand.

The study provides unique learning for practitioners, educators and researchers to understand the consumer behavior of mobile users. This will help marketers create factors that stop consumers from switching brands and develop strategies to retain customers.

Machine learning (ML) analytical tools are increasingly being considered as an alternative quantitative methodology in management research. This paper proposes a new approach for uncovering the antecedents behind product and product–service innovation (PSI).

The ML approach is novel in the field of innovation antecedents at the country level. A sample of the Equatorian National Survey on Technology and Innovation, consisting of more than 6,000 firms, is used to rank the antecedents of innovation.

The analysis reveals that the antecedents of product and PSI are distinct, yet rooted in the principles of open innovation and competitive priorities.

The analysis is based on a sample of Equatorian firms with the objective of showing how ML techniques are suitable for testing the antecedents of innovation in any other context.

The novel ML approach, in contrast to traditional quantitative analysis of the topic, can consider the full set of antecedent interactions to each of the innovations analyzed.

To endure and cope in the rapidly changing environment, it is required of firms to gain a deeper acquisition of knowledge on market dynamics and subsequently concentrate on corporations' capacity to create, restructure and integrate their internal and external competences. Hence, the objective of this study is to investigate the influence of eco-dynamic capability (EDC) on the sustainability performance of small and medium-sized enterprises (SMEs).

Structured questionnaires were used to obtain primary data. The data were solicited from 500 employees and owner-managers of SMEs. The study’s hypotheses were tested using standard multiple regression through IBM SPSS Statistics (version 24).

The study revealed that EDC has a substantial positive effect on the economic, social and environmental sustainability performance dimensions.

The focus of this study is on EDC. Thus, although dynamic capability has been the subject of substantial study, little is known regarding the effect of EDC on the economic sustainability performance (ESP) (financial), environmental sustainability performance (ENSP) and social sustainability performance (SSP) of SMEs, predominantly amongst SMEs in emerging economies.

The main purpose of this paper is to examine the adoption of big data analytics (BDA) in the Tanzania banking industry by investigating the influence of technological, environmental and organizational (TOE) factors while exploring the moderating role of perceived risk (PR).

The study employed a qualitative research design, and the research instrument was developed using per-defined measurement items adopted from prior studies; the items were slightly adjusted to fit the current context. The questionnaires were distributed to top and middle managers in selected banks in Tanzania using the snowball sampling technique. Out of 360 received responses, 302 were considered complete and valid for data analysis. The study employed partial least squares structural equation modeling (PLS-SEM) to examine the developed conceptual framework.

Top management support and financial resources emerged as influential organizational factors, as did competition intensity for the environmental factors. Notably, bank size and perceived trends showed no significant impacts on BDA adoption. The study's novelty lies in revealing PR as a moderating factor, weakening the link between technological readiness, perceived usefulness and the intent to adopt BDA.

This study extends literature by extending the TOE model, through examining the moderating roles of PR on technological factors. Furthermore, the study provides useful managerial support for the adoption of BDA in banking in emerging economies.

Artificial intelligence (AI) offers many benefits to improve predictive marketing practice. It raises ethical concerns regarding customer prioritization, market share concentration and consumer manipulation. This paper explores these ethical concerns from a contemporary perspective, drawing on the experiences and perspectives of AI and predictive marketing professionals. This study aims to contribute to the field by providing a modern perspective on the ethical concerns of AI usage in predictive marketing, drawing on the experiences and perspectives of professionals in the area.

The study conducted semistructured interviews for 6 weeks with 14 participants experienced in AI-enabled systems for marketing, using purposive and snowball sampling techniques. Thematic analysis was used to explore themes emerging from the data.

Results reveal that using AI in marketing could lead to unintended consequences, such as perpetuating existing biases, violating customer privacy, limiting competition and manipulating consumer behavior.

The authors identify seven unique themes and benchmark them with Ashok’s model to provide a structured lens for interpreting the results. The framework presented by this research is unique and can be used to support ethical research spanning social, technological and economic aspects within the predictive marketing domain.

La Inteligencia Artificial (IA) ofrece muchos beneficios para mejorar la práctica del marketing predictivo. Sin embargo, plantea preocupaciones éticas relacionadas con la priorización de clientes, la concentración de cuota de mercado y la manipulación del consumidor. Este artículo explora estas preocupaciones éticas desde una perspectiva contemporánea, basándose en las experiencias y perspectivas de profesionales en IA y marketing predictivo. El estudio tiene como objetivo contribuir a la literatura de este ámbito al proporcionar una perspectiva moderna sobre las preocupaciones éticas del uso de la IA en el marketing predictivo, basándose en las experiencias y perspectivas de profesionales en el área.

Para realizar el estudio se realizaron entrevistas semiestructuradas durante seis semanas con 14 participantes con experiencia en sistemas habilitados para IA en marketing, utilizando técnicas de muestreo intencional y de bola de nieve. Se utilizó un análisis temático para explorar los temas que surgieron de los datos.

Los resultados revelan que el uso de la IA en marketing podría tener consecuencias no deseadas, como perpetuar sesgos existentes, violar la privacidad del cliente, limitar la competencia y manipular el comportamiento del consumidor.

El estudio identifica siete temas y los comparan con el modelo de Ashok para proporcionar una perspectiva estructurada para interpretar los resultados. El marco presentado por esta investigación es único y puede utilizarse para respaldar investigaciones éticas que abarquen aspectos sociales, tecnológicos y económicos dentro del ámbito del marketing predictivo.

人工智能（AI）为改进预测营销实践带来了诸多益处。然而, 这也引发了与客户优先级、市场份额集中和消费者操纵等伦理问题相关的观点。本文从当代角度深入探讨了这些伦理观点, 充分借鉴了人工智能和预测营销领域专业人士的经验和观点。旨在通过现代视角提供关于在预测营销中应用人工智能时所涉及的伦理观点, 为该领域做出有益贡献。

本研究采用了目的性和雪球抽样技术, 与14位在人工智能营销系统领域具有丰富经验的参与者进行为期六周的半结构化访谈。研究采用主题分析方法, 旨在深入挖掘数据中显现的主要主题。

研究结果表明, 在营销领域使用人工智能可能引发一系列意外后果, 包括但不限于加强现有偏见、侵犯客户隐私、限制竞争以及操纵消费者行为。

本研究通过明确定义七个独特的主题, 并采用阿肖克模型进行基准比较, 为读者提供了一个结构化的视角, 以解释研究结果。所提出的框架具有独特之处, 可有效支持在跨足社会、技术和经济领域的预测营销中展开的伦理研究。

This article explores the emergence of organizational digital transformation in the rapidly advancing technological era. It discusses the origins, driving forces, strategies, challenges and broader implications.

The article employs a scoping review methodology that synthesizes knowledge from the existing literature, research, case studies and other relevant sources.

The findings underscore the pivotal role that organizational digital transformation plays in an era of relentless technological advancement. Leadership, organizational culture and technological enablers are identified as crucial drivers of innovation and competitiveness within organizations. The article also emphasizes ethics as a crucial element of digital transformation, focusing in particular on concerns about data privacy and the morality of artificial intelligence. Additionally, the author talks about anticipated future trends that are anticipated to influence the future of digital transformation, such as the growing influence of artificial intelligence, the trend toward hyper-personalization and the emergence of quantum computing.

The assessment has failed to provide recommendations for the actual implementation because it has mainly concentrated on conceptual and strategic aspects. Furthermore, it does not clearly define the criteria for choosing real-world examples, which limits the representation of the different industries, size ranges of organizations and outcomes associated with digital transformation.

The article stresses the significance of paying attention to the forces driving digital transformation while navigating ethical and societal concerns. In addition to highlighting the importance of anticipating future trends for strategic planning in the rapidly changing digital landscape, it emphasizes the advantages as incentives for organizations to invest in digital initiatives.

The investigation demonstrates how technology contributes to progress while posing complex ethical and change management issues. In light of increased connectivity, data analytics and artificial intelligence, it highlights the crucial need for societal adaptability and highlights the crucial role that cooperative human–machine coexistence plays in responsible development and transformative societal evolution.

The article stands out because it examines organizational digital transformation in-depth while considering its historical roots, ethical implications and future prospects. It is a priceless contribution to the field because real-world case studies and a scoping review provide a distinctive viewpoint and a comprehensive view of the effects of digital transformation on organizations and society.

The human resource and talent management fields have been increasingly focusing on the process and criteria to identify employees’ potential for career advancement due to their impact on the competitive advantage of organizations. This paper expands the extant theoretical and empirical evidence regarding these complex decisions, namely through the combined analysis of multidimensional sources of employees' capital.

This is a cross-sectional study. Data were collected from 384 individuals assessed by their line managers. The research model and hypotheses were tested using structured equation modeling.

The results show a positive and significant influence of four employees’ capital sources, namely: human capital (what you know), social capital (whom you know), psychological capital (who you are) and reputational capital (how others perceive us) with regard to judgments of potential for career advancement. The model explains 52% of the total variance in those judgments.

The data were collected using a questionnaire at a single point in time and thus, not allowing cause-effect inferences.

The results provide guidance to organizational leaders to improve the decision-making process regarding judgments of potential for career advancement.

To our knowledge, this is the first study to examine managers’ judgments regarding the potential for career advancement using four sources of employees' capital: human, social, psychological and reputational capital. Furthermore, it considers that reputation plays a mediation role.

:在人力資源和人才管理的領域裡,越來越多的焦點被放在找出員工職業發展所需潛能的過程和標準上,這是因為機構和組織的競爭優勢會受其影響。本文擬擴展關於這類複雜的判斷和決定的現存理論和經驗證據; 研究人員使用的方法為對員工資本的多維來源進行綜合分析。

:本研究為橫斷面研究。數據來自384 名受其直線經理評估的個別員工; 研究人員使用了結構方程模型,去測試其研究模型和各個假設。

:研究結果顯示,就員工職業發展所需潛能的判斷而言,存在著會帶來正面和重大影響的四個員工資本來源,這包括人力資本 (你所瞭解的事物) 、社會資本 (你所認識的人物) 、心理資本 (你是誰) 和聲譽資本 (我們予人的印象) 。有關的模型可說明判斷百分之五十二的總方差。

:由於數據的收集是於單一時間點和透過問卷調查而完成的,故未能收因果推斷的效果。

:研究結果給予組織領袖實際的指引,使他們在關於職業發展所需潛能的判斷上，能夠改善其決策的過程。

:就我們所知,本研究為首個研究、以四個員工資本來源,即人力資本、社會資本、心理資本和聲譽資本,去探討經理如何就職業發展所需的潛能作出判斷; 而且，本研究認為聲譽是扮演著調節角色的。

For Bangladeshi small and medium enterprises (SMEs), the COVID-19 economic shock is remarkable in both its complexity and intensity. SMEs need systemic inspiration to solve the crisis, aligned with a moral and authentic approach that serves both the leader and the follower’s interests. This study aims to conceptualize the innovation-focused success method of SMEs before and after the pandemic to manage the crisis by establishing spiritual leadership based on Islamic perspectives.

To discuss the impact of spiritual leadership on innovation-focused SME performance configuration through the lens of a crisis, a comprehensive literature study has been carried out in which over 360 articles are read and reviewed by the authors. It has also established the reliability and validity of literature analysis. Also, a qualitative investigation has been used to support the direction of the study.

For a subsequent process of scientific deployment and evaluation of its execution, a new applied strategic innovation-focused SME success configuration through spiritual leadership development is made available. The primary value of this paradigm is the potential to calculate and treat the aspects of spiritual leadership obtained from Islamic ideas.

Prior analytical or empirical attempts from multiple viewpoints are subsequently needed to inquire about the proposed conceptualization.

Among the realistic consequences of this analysis is that while a number of leadership paradigms have been embraced by a broad body of leadership studies, the findings indicate that this paper should pay heed to the influential spiritual style of leadership, taking into account Islamic perspectives on the context of crisis. Therefore, Bangladeshi SMEs need to develop and run leadership training programs focused on the Islamic viewpoint of spirituality to encourage the actions of leaders during and after crises.

The legal and moral values of the society would ultimately be upgraded from this conceptualization. Moreover, less corruption in corporate activities would improve the economic prosperity of a nation. It would also contribute to the cross-cultural portrayal of the positive picture of Islam.

This holistic conceptualization describes the mediating role of strategic innovation practices based on theoretical foundations, which have seldom been done in previous research, between the Islamic model of spiritual leadership and SME success during and after a crisis.

Building on the resource-based view (RBV) and the theory of other orientation, this study aims to examine the association between Islamic work ethics (IWEs) and organizational performance highlighting the role of employee relations climate as an underlying mechanism.

Data were collected from 239 employees working in diverse sectors in the state of Qatar. Structural equation modeling of partial least squares was used to analyze the data of the study.

The results suggest that IWEs positively impact organizational performance and employee relations climate. Furthermore, employee relations climate demonstrated to play a mediating role in the IWEs-organizational performance link.

The study can be used by administrators pertaining to the importance of IWE and employee relations climate to cultivate higher organizational outcomes such as organizational performance.

This research is distinctive as it examines the connection between IWEs and organizational performance in Qatar, a country where the influence of Islamic values and beliefs on work ethics is profound. In addition, the research sheds light on a topic that has received little attention in the literature: the significance of the workplace climate in determining how IWEs affect organizational performance. Finally, the research integrates two important theoretical frameworks, the RBV and the theory of other orientation, to create a comprehensive model that explains the complex relationship between IWEs, employee relations climate and organizational performance.

The efficiency of each of an organization’s individual workers determines its effectiveness. The study aims to explore the relationship between human resource management (HRM) practices and organizational effectiveness with employee performance as a mediating variable.

Data were collected from 800 police officers in the Greater Accra and Tema regions. The data were supported by the hypothesized relationship. Construct reliability and validity was established through confirmatory factor analysis. The proposed model and hypotheses were evaluated using structural equation modeling.

The results show that career planning and employee performance were significantly related. Self-managed teams and employee performance were shown to be nonsignificantly related. Similarly, performance management and employee performance were shown to be nonsignificantly related. Employee performance significantly influenced organizational effectiveness. The results further indicate that employee performance mediates the relationship between HRM practices and organizational effectiveness.

The generalizability of the findings will be constrained due to the research’s police service focus and cross-sectional data.

The study’s findings will serve as valuable pointers for the police administration in the adoption, design and implementation of well-articulated and proactive HRM practices to improve the abilities, skills, knowledge and motivation of officer’s to inordinately enhance the effectiveness of the service.

By evidencing empirically that employee performance mediates the relationship between HRM practice and organizational effectiveness, the study extends the literature.