Business Settings Research Articles

A self-regulatory adapting mechanism to changing work setting: Roles of playful work design and ambidexterity

In today's uncertain business setting, the intensity of rivalry amongst service firms requires a high level of quality and adaptability from service staff to fulfill increasing customer needs and wants. Indeed, every individual's ability to adjust to changing demands is vital for management to promote within their companies. The present study proposes and tests a novel self-regulatory adapting mechanism to examine the conditions within which service staff might activate their ambidextrous behavior which can be beneficial for their proactive service performance. Based on Trait Activation theory (TAT), Individual Adaptability Theory, and Job demands-resources theory, we analyze the direct and mediating effects of certain personal characteristics (Proactive Personality) and initiatives (Playful work design and Uncertainty adaptability) to activate the ambidextrous mode of employees toward higher proactive service performance. To test our hypotheses, we collected survey data from 368 frontline banking employees in all three regions of Vietnam. Practically, the results and recommendations from this study will assist in the hands-on management and motivation of service representatives toward better proactive performance.

ОРГАНІЗАЦІЯ ТА ЕФЕКТИВНІСТЬ МОНІТОРИНГУ ДІЯЛЬНОСТІ ПІДПРИЄМСТВА

In contemporary business settings, it's essential to establish a dynamic information and analytical framework to facilitate effective managerial decisions. This involves implementing a monitoring system to track internal processes and external factors, providing comprehensive and timely data for decision-making. The article aims to outline the theoretical and methodological underpinnings of such a monitoring system, focusing on its practical application in monitoring, diagnosing, modeling, and managing various aspects of a company's operations. Drawing from scholarly works and diverse sources, including periodicals and online materials, the study employs methods such as comparative analysis and content analysis. It argues that modern enterprise monitoring should not merely be an information system but should also serve as a vital support for informed decisionmaking. The article proposes a two-level monitoring system comprising an information base and methodological framework to fulfill evaluation, analytical, prognostic, and management functions. It identifies and examines the structural components of this system, including the database and knowledge base. Furthermore, it defines key elements such as goals, objects, subjects, principles, and functions, forming the conceptual foundation of the monitoring system. Building upon these foundations, the article presents a model for the enterprise's monitoring system as an integral part of the decision-making process. The practical significance of this conceptual model lies in its ability to develop a comprehensive system for monitoring, evaluating, and forecasting enterprise activities, thereby facilitating timely management decisions. Effective implementation of such a system requires robust technological infrastructure, skilled personnel, and organizational commitment to data-driven decision-making practices. Additionally, ongoing evaluation and refinement are necessary to adapt the monitoring system to evolving business environments and information needs. Overall, the integration of advanced monitoring capabilities into managerial processes enhances agility, resilience, and competitiveness in today's dynamic business landscape.

Identifying Critical Success Factors in Supply Chain Performance

Because of the rapidly changing business environment, companies must have the ability to quickly respond to environmental changes in order to survive. This study explores supply chain critical success factors in supply chain performance. In this paper we review the relevant literature and establish related hypotheses. For the purpose of data collection, a survey form is developed based on the constructs for the study model. The questionnaire is designed using a five point Likert scale and administered to respondents. Total valid responses of 337 are used for this study purpose. Descriptive statistics of independent and dependent variables are identified. A regression analysis is conducted for model parameter estimates of supply chain performance with supply chain critical success factors. Study findings show that management may be in a better position dealing with CEO leadership commitment, customer information sharing, supply stability and flexibility, and supplier operational integration, in order. This study is expected to provide supply chain managers and relevant decision-makers with strategic insights for improving decision-making in a supply chain environment and other similar business settings.

Social business environment and transnational corporations’ loyalty: the executives’ perceptions in Tanzania

The economic growth of the host low-income countries, which depends on foreign investments, among other things, has been impacted by the disloyal behaviours of foreign firms, including transnational corporations (TNCs). The demonstrated disloyal behaviours include the closure of operations and productions, scaling back expansion plans, and shifting income-generating operations to other countries with favourable business settings. This study examines the influence of the social business environment (SBE) on TNCs loyalty towards the host country, Tanzania. A cross-sectional design was employed to collect data from 131 TNCs in Tanzania using a structured questionnaire. The hypotheses were tested by hierarchical regression analysis. Findings reveal that the SBE has a positive and significant effect on TNCs loyalty through social attitudes, language, consumer preferences, and attitudes towards foreign businesses. Other dimensions of SBE, including age structure, gender roles, and the population’s literacy level, have negative and insignificant effects. Among all dimensions of the SBE, language is the best predictor of TNCs loyalty in Tanzania, followed by social attitudes, customer preferences, and attitudes of society towards foreign businesses. Based on the results, it is suggested that policymakers establish consistent social policies that encourage favourable social attitudes and beliefs, local and international language usage and proficiency, predictable customer preferences, and amicable attitudes of society towards foreign businesses to stimulate high TNC loyalty in Tanzania, which is crucial for sustainable economic development.

CROSS-CULTURAL BUSINESS COMMUNICATION: A LINGUISTIC AND COGNITIVE PERSPECTIVE

In the modern global business sphere, the necessity for effective cross-cultural communication has become paramount. The article navigates the intricate interplay between language, cognition, and culture within the globalized business landscape. It offers a comprehensive view of the multifaceted complexities that underpin successful cross-cultural interactions, drawing from an extensive review of scholarly works and theoretical frameworks. Beginning with an exploration of culture’s influence on communication styles and norms, it proceeds to highlight the role of language in facilitating effective cross-cultural communication. By comparing managerial preferences across diverse cultural contexts, the study offers a nuanced understanding of cultural variations and their impact on negotiation tactics, team dynamics, and relationship-building within international business settings. Furthermore, the article sheds light on the cognitive dimensions of culture, emphasizing the need for adaptable training methodologies to bridge cultural gaps. It extends discussions to encompass the societal, political, and technological dimensions of cross-cultural interactions, underscoring the critical significance of understanding and respecting these differences to foster successful global partnerships. Through this holistic examination, the article reinforces the critical importance of linguistic and cognitive perspectives in navigating the complex web of cross-cultural communication. It provides pragmatic guidance for businesses and individuals engaged in international collaborations, highlighting the necessity for sensitivity, adaptability, and nuanced approaches to bridge diverse cultural contexts, ultimately shaping the future of successful global partnerships.

Addressing Managerial Loss Aversion for the Corporate Value Creation Process: A Critical Analysis of the Literature and Preliminary Approaches

To date, the studies on managerial loss aversion have produced contradictory findings, making it impossible to: (i) identify the ultimate impact of managerial loss aversion on the value that organisations create for themselves and for their stakeholders, and (ii) mitigate the effect of managerial loss aversion to improve corporate value creation. With the aim of filling this gap, the authors of this paper first performed a Systematic Literature Review (SLR), resulting in 65 relevant papers. The 65 papers were then analysed through a Thematic Analysis (TA), which was aimed at isolating and revising the single effects of managerial loss aversion on the corporate value creation process. Once it became clear when and how managerial loss aversion leads to negative impacts on corporate value creation (such as suboptimal investments in corporate social responsibility, short-term-oriented budget expenditures, illegal corporate conduct in favourable contexts, and low demand for audit quality), a novel theoretical framework was built. This framework proposes some preliminary approaches to mitigate these detrimental effects. In particular, future empirical research may operationalise potential debiasing strategies, derived from critical analysis of the literature, to reduce managerial loss aversion in different business settings, thereby improving corporate value creation.

Unleashing the digital barrier: Obstacles and challenges of digital transformation amidst technological roadblocks

The widespread adoption of digital technologies in enterprises remains limited, prompting concerns over the sluggish pace of technological integration. Numerous articles emphasize the urgency of accelerating digital transformation and embracing new technologies. This paper focuses on identifying and examining obstacles hindering the effective utilization of digital tools and technologies in business settings. It conducts a comprehensive assessment of two primary aspects - external and internal factors - through a combination of secondary research and a comparative analysis of primary research findings. The research draws on data from diverse sources, including the ESTAT data repository, surveys on Information and Communication Technology (ICT) usage and e-commerce in enterprises, and the European Commissions report on Small and Medium-sized Enterprises (SMEs), start-ups, scale-ups, and entrepreneurship. By shedding light on these obstacles, this paper aims to provide valuable insights that can facilitate the successful implementation of digital technologies in enterprises.

Virtual Reality (VR) Technology in Foreign Language Training for Indonesia's SMEs Actors

This article evaluates the integration of virtual reality (VR) technology in foreign language training for SMEs in Indonesia using the Kirkpatrick Model. The study involved SME actors from various industries who participated in a tailored VR language training program. Surveys and interviews were conducted to assess participants' reactions, perceptions, and relevance to language learning goals. The evaluation measured learning outcomes such as improved language proficiency and increased confidence in using foreign languages in business settings. The study also investigated behavioral changes resulting from VR training, including language skills application in daily business activities and communication strategies with international partners or customers. The overall impact of the program on SMEs' competitiveness, market expansion, and international collaboration was evaluated. The findings indicate that the VR training program was effective, with positive reactions, learning outcomes, and behavioral changes in business activities. The study emphasizes the importance of measuring reactions and suggesting improvements in training materials and implementation schedules based on participant feedback. The VR-based language training program holds promise for enhancing SMEs' language skills, competitiveness, and internationalization efforts.

Key Factors influencing Organizational Commitment

Research on organizational commitment is widely conducted worldwide and is regarded as one of the most significant factors. This is due to research showing that organizational commitment, in both business and government settings, significantly affects organizational success indicators. This study aimed to investigate significant variables influencing organizational commitment through a review of relevant literature and research. The study’s conclusions indicate that job satisfaction, job experience, work environment, and management team leadership are the four key variables that have a significant impact on organizational commitment. Consequently, in order to foster employee commitment to the organization, management of the company should focus on these four factors. Because it has an impact on both the employees and the organization itself, developing organizational commitment in employees is crucial. Making employees happy at work and wanting to work for the company for a long time is one way that organizational commitment affects employees. There will be a decline in the turnover rate. Organizational commitment will have a direct impact on the organization itself in the form of lower human resource management expenses, ongoing employee development, higher employee skill levels, and the ability for the organization to grow steadily and more sustainably.

How is counterfactual thinking integrated in organizational risk and resilience practices?

Managing risk from natural hazards and other types of critical risks is fundamental to the viability, sustainability, and resilience of organizations of all types and sizes. It is, crucially, an important part of demonstrating their purpose and commitment to society and the broader environment, which incorporates what they do to help tackle climate change. Counterfactual thought is the process of reimagining the past, for example, for a particular event that has occurred, as being different than what actually transpired. In this study, we investigate how this process and mindset of counterfactual thinking can have specific value in helping people in organizations to have a more robust way of analyzing and managing risk. The role and potential impact of counterfactual-based practices on risk mitigation and management, and an increased focus on purposeful resilience in a business context, has not previously been widely studied. We have conducted 10 semi-structured interviews with people in senior positions in various organizations, global contexts, scales, covering a range of industries and sectors including construction and property, engineering, mining, nonprofit, and consulting. Through these interviews we identify: (1) existing challenges of current risk management systems; (2) types of risks of concern in the organizations interviewed; (3) the current and potential use of counterfactual practices in these organizations; and (4) the perceived value of counterfactual practices within the business setting for risk mitigation and resilience. We share best practices that emerged from the study, especially the role of leadership, diversity, and inclusion as a necessary foundation for successful implementation of counterfactual risk practices. The findings from this project can be used to inform businesses interested in adopting emerging downward counterfactual risk and resilience practices to improve their preparedness to manage critical and evolving risks.

Empowering Decision Support System and Social Change: 'Leadership as the Change Agent'—Investigating the Mediating Role of Information Management Culture in Technological Innovation and Socioeconomic Development as Moderation

In contemporary business settings, the ability to sustain a competitive advantage is contingent upon two pivotal factors: organizational performance and technological innovation. Comprehending the determinants that propel these results is imperative for achieving success within an organization. The objective of this investigation is to scrutinize the interconnections among decision-making autonomy, leadership style, change readiness, and information management culture, and their effects on both organizational performance and technological innovation. Furthermore, the research investigates the intermediary function of information management culture and the moderating impact of socioeconomic development. The present investigation employs a quantitative research methodology utilizing a cross-sectional design. The study utilizes a purposive sampling method to choose a sample of 430 bank employees from diverse banks in China. A survey instrument is employed to assess the variables of interest, which have been derived from prior research. The study's results indicate that the level of decision-making autonomy has a noteworthy and favorable influence on both the performance of an organization and its technological innovation. The study reveals that change readiness has a noteworthy and favorable influence on the performance of an organization. Additionally, the culture of information management displays a significant and positive correlation with both technological innovation and organizational performance. The research also highlights the role of information management culture as an intermediary factor that influences the relationship between decision-making autonomy and both organizational performance and technological innovation. Additionally, the study reveals the moderating impact of socioeconomic development on the correlation between information management culture and organizational performance.

“Shared decision-making” for prostate cancer screening: Is it a marker of quality preventative healthcare?

Background“Shared decision-making” (SDM) is a cornerstone of prostate cancer (PCa) screening guidelines due to tradeoffs between clinical benefits and concerns for over-diagnosis and over-treatment. SDM requires effort by primary-care-providers (PCP) in an often busy clinical setting to understand patient preferences with the backdrop of patient risk factors. We hypothesized that SDM for PCa screening, given its prominence in guidelines and practical challenges, may be associated with quality preventative healthcare in terms of other appropriate cancer screening and encouragement of other preventative health behaviors. MethodsFrom the 2020 Behavioral Risk Factor Surveillance Survey, 50–75 year old men who underwent PSA screening were assessed for their participation in SDM, PCa and colorectal cancer (CRC) screening, and other preventative health behaviors, like vaccination, exercise, and smoking status. Adjusted odds ratio of likelihood of PSA testing as a function of SDM was calculated. Likelihoods of SDM and PSA testing as a function of preventative health behaviors were also calculated. ResultsScreening rates were 62 % for PCa and 88 % for CRC. Rates of SDM were 39.1 % in those with PSA screening, and 16.2 % in those without. Odds of PSA screening were higher when SDM was present (AOR = 2.68). History of colonoscopy was associated with higher odds of SDM (AOR = 1.16) and PSA testing (AOR = 1.94). Health behaviors, like regular exercise, were associated with increased odds of SDM (AOR = 1.14) and PSA testing (AOR = 1.28). History of flu vaccination (AOR = 1.29) and pneumonia vaccination (AOR = 1.19) were associated with higher odds of SDM. Those who received the flu vaccine were also more likely to have PSA testing (AOR = 1.36). Smoking was negatively associated with SDM (AOR = 0.86) and PSA testing (AOR = 0.93). Older age was associated with higher rates of PSA screening (AOR = 1.03, CI = 1.03–1.03). Black men were more likely than white men to have SDM (AOR = 1.6, CI = 1.59 – 1.6) and decreased odds of PSA testing (AOR = 0.94, CI = 0.94 – 0.95). ConclusionsSDM was associated with higher odds of PSA screening, CRC screening, and other appropriate preventative health behaviors. Racial disparities exist in both SDM and PSA screening usage. SDM may be a trackable metric that can lead to wider preference-sensitive care and improved preventative care.

Assessment of the Production Process Organization in the Metal Industry - Case Study

Abstract The article provides a detailed case study illustrating the practical application of BOST surveys while focusing on the third principle of Toyota. This particular principle underscores the importance of achieving an even distribution in production to mitigate fluctuations and ensure the smooth functioning of the production process. The article delves into a comprehensive analysis of how this principle is implemented in real-world scenarios, exploring its effects on production efficiency and elucidating the advantages gained from the elimination of downtime and the prevention of excessive inventory buildup. Moreover, the article offers a discussion on examples of applications across various industries, shedding light on practical strategies for implementing the third Toyota principle. The goal is to not only optimize production processes but also enhance flexibility and adaptability to evolving demand patterns. The article concludes by examining the pivotal role of this principle within the broader context of operational excellence and the development of more efficient production systems. The research in focus centers around a company operating in the metal industry. Through the utilization of BOST questionnaire surveys, production workers within the company expressed their perspectives, revealing which factors they deemed most crucial. The analysis of research results takes various forms, including tables, histograms, radar charts, and several statistical tools. The overarching objective of this analysis is to identify and present the most critical factors by constructing significance sequences based on the obtained results. The findings obtained for small and medium-sized enterprises align with results from similar tests conducted in different business settings, indicating a level of consistency and applicability across various organizational contexts.

Applying the reference values of real-ear-to-coupler-difference for deaf and hard-of-hearing children in Taiwan: Cautions and considerations.

Measurement of real-ear-to-coupler differentials (RECDs) is a critical part of the hearing aid (HA) verification process. This study examines the validity of reference RECD values preset by the HA analyzer, Audioscan RM500, for deaf-and-hard-of-hearing (DHH) children in Taiwan. RECD measurements were performed on 658 ears of DHH children. A linear mixed model was used to analyze the reference and measured RECD values. The findings revealed slight disparities between normative RECD values from North America and those observed in Taiwanese DHH children. While generally small (less than 5 dB), these differences imply potential challenges in achieving optimal HA fitting in specific scenarios. Therefore, we recommend individualized RECD/REM measurements for cases of poor auditory performance, certain frequency ranges, or notable variations in ear canal volume. From a clinical perspective, while broadly applicable, the use of North American RECD normative data in Taiwan requires cautious consideration of potential minor variations. This study contributes to current knowledge by affirming the use of a Western RECD database for Taiwanese DHH children. However, we underscore the ongoing importance of individualized HA fitting strategies, particularly for cases with stagnant intervention progress. While built-in RECD reference values can offer preliminary fitting guidance, especially in busy clinical settings, our study sheds light on the circumstances where caution is essential. Audiologists can efficiently allocate their time and effort by focusing on personalized RECD measurements for cases exhibiting suboptimal intervention outcomes, thereby effectively optimizing HA gain settings.

A Review on Mianzi in Interpersonal, Familial, and Business Settings

Face is one of the crucial cultural aspects in Chinese society, which can be separated into mianzi and lian. This article will focus on summarizing the concept of mianzi. It is tied to social occasions that require interpersonal communication between individuals and groups: face culture can be found in both workplaces and individual settings. Face culture is adopted as a primary social principle in China and it plays an important role in affecting the languages and behaviors of Chinese people. Thus, being able to understand the meaning of mianzi and behave accordingly is important for corporations that plan to do business in China and individuals who seek connection with Chinese society or culture in any form. This paper will summarize the most important facets of Chinese face culture regarding its role in interpersonal, familial, and business settings, as they are essential to the understanding of face culture.

Statistical Model Checking in Process Mining: A Comprehensive Approach to Analyse Stochastic Processes

The study of business process analysis and optimisation has attracted significant scholarly interest in the recent past, due to its integral role in boosting organisational performance. A specific area of focus within this broader research field is process mining (PM). Its purpose is to extract knowledge and insights from event logs maintained by information systems, thereby discovering process models and identifying process-related issues. On the other hand, statistical model checking (SMC) is a verification technique used to analyse and validate properties of stochastic systems that employs statistical methods and random sampling to estimate the likelihood of a property being satisfied. In a seamless business setting, it is essential to validate and verify process models. The objective of this paper is to apply the SMC technique in process mining for the verification and validation of process models with stochastic behaviour and large state space, where probabilistic model checking is not feasible. We propose a novel methodology in this research direction that integrates SMC and PM by formally modelling discovered and replayed process models and apply statistical methods to estimate the results. The methodology facilitates an automated and proficient evaluation of the extent to which a process model aligns with user requirements and assists in selecting the optimal model. We demonstrate the effectiveness of our methodology with a case study of a loan application process performed in a financial institution that deals with loan applications submitted by customers. The case study highlights our methodology’s capability to identify the performance constraints of various process models and aid enhancement efforts.

Toward a multilevel framework of multicommunicating: Insights from a systematic review

With the rise of smartphones, social media, and various digital communication platforms, multicommunicating (MC) has become prevalent, where individuals simultaneously engage in multiple communication tasks using information and communication technologies. However, the existing research on MC is fragmented and lacks a comprehensive understanding of its implications for and consequences on individuals and groups in various work, personal, and social contexts. This study proposes a multilevel framework to address these gaps and provides insights into the dynamics of MC at different levels: individual communicators, dyadic relationships, group dynamics, and the broader communication network. Through a systematic review of MC studies published in the last two decades, we identified trends in publication characteristics and research contexts. Existing research was conducted in educational, business, and social settings. Most studies focused on individual-level mechanisms and impacts, with findings indicating that MC negatively affects task performance, learning satisfaction, and psychological engagement. Additionally, our review examined the influence of MC on dyadic outcomes, such as social evaluation and communication partner satisfaction. Based on the review, we identified gaps and proposed future research directions to enhance our understanding of MC. By adopting a multilevel perspective, this study contributes to a more comprehensive understanding of MC, encompassing individual-level processes, social dynamics, and even a few emerging network effects.

Deep Learning-based Automated Knee Joint Localization in Radiographic Images Using Faster R-CNN.

Osteoarthritis is a condition that poses a risk to the knee joint, resulting in pain and impaired function. However, traditional knee X-ray evaluations using the Kellgren-Lawrence grading system have proven to be inefficient. These evaluations are subjective, time-consuming, and labor-intensive, particularly in busy hospital settings. The objective of this research was to present a deep learning-based approach that can detect knee joint regions in medical images. By addressing the limitations of traditional methods, the aim was to develop a more efficient and automated approach for knee joint analysis. The proposed method utilizes the Faster R-CNN model, which consists of a region proposal network (RPN) and Fast R-CNN. The RPN generates region proposals that potentially contain knee joint regions, while the Fast R-CNN network categorizes and extracts features from these proposals. To train the model, a dataset of knee joint images was employed. The performance of the model was evaluated using metrics, such as accuracy, precision, recall, F1-score, and mean IoU (Intersection Over Union). The results demonstrated the high accuracy of the proposed method in detecting knee joint regions. The model achieved a mean IoU of 94.5, indicating a strong overlap between the predicted and ground truth regions. These findings highlight the potential of deep learning-based approaches in automating medical image analysis, specifically in the diagnosis and management of knee joint disorders. This study emphasizes the significance of leveraging advanced technologies, such as deep learning, in medical imaging. By developing more efficient and accurate methods for identifying knee joint regions in medical images, it becomes feasible to enhance patient outcomes and healthcare delivery. The proposed deep learning-based approach showcases promising results, paving the way for further advancements in the field of medical image analysis and contributing to improved diagnostic capabilities for knee joint disorders.

An empirical investigation of social comparison and open source community health

AbstractIt is well known that corporations rely on open source software as part of their product development lifecycle. Given these commitments, understanding the health of open source communities is a central concern in today's business setting. Our research uses social comparison theory as a framework for understanding how open source communities consider community health beyond any single metric within any single open source community—including a broader view of how others are using these health indicators in practice. Using methods from engaged field research, including 38 interviews, we examine practices of social comparison as an advancement in understanding open source community health—and subsequently engagement with open source communities. The results of this study show that open source community health is not a single set of discrete metrics but is an ongoing social construction. Through our study, we advance theoretical and applied knowledge regarding issues of open source community health, open source community engagement, and social comparison.

AI in Decision Making: Transforming Business Strategies

Artificial intelligence has developed as a phenomenon greatly influencing numerous corporate sectors, particularly in decision-making processes. AI has matured into an intrusive instrument, impacting various corporate sectors, including their essential processes like decision-making. Ongoing improvements in AI technology have assisted organizations in optimizing their operations and strategic development. This research analyzes the function of AI in decision-making and its consequent impact on the enhancement of corporate strategy. A complete literature review was done for this inquiry. This article tries to evaluate the repercussions of AI across multiple sectors and its influence on business environments. It provides cases of AI application across different sectors and a critical critique of the present literature on AI within the business setting. It also discusses the challenges a corporation may face when integrating AI technology and evaluates probable developments that influence AI in business planning. Artificial intelligence positively benefits the business sector by boosting organizational decision-making capacities, leading to superior corporate decisions. The analysis points out a number of areas where AI has considerably enhanced efficiency as well as performance measures. The fundamental constraint of the study is that the deployment of AI is dynamic, with differing development rates across different industries. additional, there are additional limits such as data privacy and ethical difficulties and considerable expenses associated to using AI. The study stresses the relevance of AI in current management and proposes that firms should implement AI solutions to generate a competitive advantage. Managers and decision makers should consider the opportunities for employing AI and the diversity of possible difficulties that may occur. The provided study is valuable since it focuses on furthering our awareness of the true nature of threats and opportunities connected with AI, as well as reviewing the influence of this technology on numerous professions. This research adds to the achievements in understanding AI in organizational strategy and gives knowledge that is beneficial for academics and practicing managers.