Diverse Business Research Articles

Uncertainty and bank risk in an emerging market: The moderating role of business models.

The paper explores the role of business models in the link between uncertainty and bank risk. From the perspective of banks, given that future outcomes tend to be less predictable if banking uncertainty rises, we highlight a framework that a larger dispersion of bank shocks to bank-specific variables might mirror such decreased predictability as a consequence of increasing uncertainty. To compensate for the persistence of bank risk and address the endogeneity issue, we applied the system generalized method of moments (GMM) estimator as the main regressions. Analyzing a panel of commercial banks from Vietnam between 2007 and 2019, we find that higher levels of banking uncertainty may increase bank risk, as gauged by banks' credit risk (loan loss reverses and non-performing loans) and default risk (Z-score index). This detrimental influence of uncertainty appears to be most pronounced with banks relying on pure lending, and it decreases with more non-interest income. A deeper investigation after estimating the marginal effects with plots reveals an asymmetric pattern that bank risk is immune to uncertainty in banks with the highest level of income diversification. Interestingly, we also provide evidence that uncertainty may lower the default risk level when income diversification exceeds a sufficiently high level. Our findings demonstrate that diversified business models are an efficient buffer against higher bank risk in times of increased uncertainty.

AI-ENABLED CUSTOMER EXPERIENCE ENHANCEMENT IN BUSINESS

This scholarly investigation delves into the transformative impact of Artificial Intelligence (AI) on enhancing customer experience in the business realm. The study's purpose was to meticulously examine the integration, evolution, and strategic implications of AI in business operations, particularly in customer engagement. A comprehensive literature review and detailed case study analysis constituted the core methodology, focusing on peer-reviewed articles and practical examples from diverse business sectors. This approach facilitated a multi-dimensional exploration, capturing both the technological advancements in AI and the associated implementation challenges within various business contexts. Central findings from this research underscore AI's evolution from an emerging technological tool to a fundamental component in customer-centric business strategies. AI's capabilities in personalizing customer interactions, automating support systems, and leveraging predictive analytics have revolutionized business-customer dynamics. However, this evolution is not without its challenges, including data privacy concerns, ethical considerations, and the need for skilled AI expertise. The study concludes that AI is a strategic asset, necessitating thoughtful integration into business models. It emphasizes the importance of a collaborative approach, where AI specialists and industry experts work synergistically to tailor AI solutions to specific business needs. Ethical considerations and maintaining customer trust are highlighted as pivotal in AI deployment strategies. The study recommends continuous innovation, investment in AI infrastructure and talent, and adherence to ethical AI practices. These measures are essential for businesses to enhance customer experiences and drive sustainable growth in the digital age
 Keywords: Artificial Intelligence, Customer Experience, Business Strategy, AI Integration, Ethical Considerations.

The role of artificial intelligence in corporate digital strategies: evidence from China

PurposeIn the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.Design/methodology/approachTo explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.FindingsThe investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.Originality/valueThis study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.

A search dilemma for market niches: Korea and Taiwan in a time of US‐China high‐tech decoupling

AbstractSouth Korea and Taiwan are nimble, mid‐sized economies known for their critical technological competencies in high‐tech industries like semiconductors. These industries have been crucial for their business diversification and specialisation. During the period of globalisation from the 1980s to the 2010s, both nations rapidly climbed the economic ladder. However, the emergence of US‐China trade tensions in the late 2010s disrupted the global landscape. The decoupling of high‐tech value chains in favour of inward‐oriented industrial policies presented a dilemma for semiconductor firms in Korea (e.g. Samsung Electronics) and Taiwan (e.g. TSMC). This paper provides an overview of recent changes in their semiconductor industries and discusses the concerns surrounding industrial value migration. It explores the strategic technological ventures taken by both economies to navigate this uncertain environment.

Business diversification choices: do director incentives matter?

PurposeMuch prior work involving director incentives and corporate behaviour has been focussing on their absolute dollar value or the intrinsic value and generated mixed findings. Comparison theories, however, suggest that the relative value of an incentive may be the main drive for individual performance. This study attempts to investigate the role of director relative pay in promoting the board’s intervention with unrelated diversification decisions.Design/methodology/approachThe analysis uses data from firms operating in more than one segment during the period from 1999 to 2019. Data were obtained from WRDS databases. Ordinary least squares (OLS) regression analysis and the two-stage system generalized method of moments (GMM) were run to test the hypotheses. To test the robustness of the findings, alternative proxies for the key independent variables were used in separate analyses.FindingsThe results support the hypothesis that unrelated diversification negatively impact firm performance, while higher director relative pay will help reduce unrelated business diversification. The absolute director pay, however, has no significant impact on corporate strategic choices. The results also highlight the moderating effect of director overcompensation. Director overcompensation will cancel out the impact of relative director pay on unrelated diversification.Originality/valueThis study takes a fresh theoretical perspective by framing the investigation using the dimensional comparison theory to address the single untended comparison framework in the director pay structure – the intra-individual framework. It is the first to investigate the role of director relative pay in corporate strategic choices. The findings support the contention that the relative value of the incentive is an important indicator of the effectiveness of the pay.

Empowering Entrepreneurship: Strategies and Challenges Faced by Saudi Women in Diverse Business Sectors

Purpose: The primary objective of this research is to investigate the strategies employed by female entrepreneurs in Saudi Arabia to overcome the challenges associated with running successful businesses across various sectors. Theoretical Framework: The literature reviews shows that the entrepreneurial endeavors of Saudi women appear to be dynamic and demanding, showcasing their resilience in choosing entrepreneurship as a career path. Design/Methodology/Approach: To conduct the analysis, a combination of qualitative and quantitative methods was utilized. Both primary and secondary data were gathered from women entrepreneurs in different states of Saudi Arabia. In-depth interviews were conducted with 100 female entrepreneurs involved in various small-scale business activities, such as apparel, fragrances, coffee shops, and boutiques. The major findings of the study is that majority of women (almost all 100 sample) taken for study have plans for future business expansion. Findings: The Saudi women also receive a lot of Government support for their business operations. It was also found that majority of Saudi women have invested more than 200000SAR initially. However, it is important to note the limitations of this research. The findings may not be readily generalizable beyond the selected sample. Research/Practical and Social Implications: The success of the Saudi Vision 2030 plan is believed to depend on a higher percentage of women in the labor force, and this objective has been achieved ten years ahead of schedule as more women are joining the workforce in recent years. Originality/Value: The article highlights the value of women's participation in business for the improvement of society at large. The study sheds light on the often-overlooked role of Saudi women as small business owners.

Succession Planning and Executive Compensation Strategies: Case Study on Multi-business Corporate Firms in India

In the age of Post COVID Resilience and Digitization, strategic issues in leadership research have gained prominence. Succession planning is one of such topics of strategic Human Resource Management (SHRM) which is considered by corporate boards as a major concern as it provides a way for business continuity. It is quite an important aspect for most of the start-up enterprises of modern times as they have to ensure its business continuity through the availability of strong leadership bench strength. Having a good successor on key management positions will ensure a family legacy for upcoming generations.Past literature offers insight that corporate firms including family and standalone groups have observed many challenges in terms of loss of leadership on key management positions due to the lack of a proper succession plan in place. In this study, it has attempted to explore various insights related to succession planning and its linkages to executive compensation in corporate firms having diversified business portfolios. Findings provide a fresh perspective on succession planning and executive compensation which is equally important for practitioners and new-age start-ups.

Realization of the potential of diversification of agricultural business to reduce the risks of sustainable development

The deepening of the global problems of human development requires new approaches to solving the strategic tasks of further existence. With this approach, under modern conditions, the concept of sustainable development appears, with the help of which it is possible to ensure the achievement of the goals of sustainable development of national economies and society. Agriculture is the primary sector of Ukraine's national economy, and the state of development largely determines the economic growth rate. In recent years, many problematic issues have accumulated in the agricultural sector, which requires intensifying the diversification processes of economic activity. The article identifies the principal risks and problems that can be solved based on directions for expanding the diversification of agrarian business, among them optimizing the sectoral balance, increasing the rationality and environmental friendliness of the use of natural resources, restoring biodiversity, reviving the human resources potential of rural areas and mitigating the consequences of inclusive gaps between rural and urban areas of the country. The composition of the potential for diversification of economic activity of agrarian business entities based on sustainable development is substantiated. Among the main elements proposed are food security, climate neutrality and preservation of biological resources, inclusiveness of development of rural areas, and economic opportunities. The analysis of the production structure of agriculture showed the dominance of crop production and a decrease in the share of livestock production. Based on the results of the conducted research, it is proposed to consider the diversification of agrarian business as a way of restoring and ensuring the biodiversity of crops and animals, which is based on the principles of rational use of bioresource agricultural potential to achieve the goals of sustainable development of agriculture and rural areas. The fundamental principles of diversification of economic activities of agricultural enterprises based on sustainable development were defined as eco-tolerance of agricultural production, food sufficiency, inclusiveness, achievement of sectoral balance of agricultural production, efficiency, improvement of the level of well-being and quality of the country's population. Keywords: diversification, agriculture, rural areas, development, opportunities.

A Study on Conflict Management in Contracting-out in Public Services

This research explores the dynamics of outsourced labor while specifically analyzing personnel expense proportions in various business categories. Utilizing a Quadrant Framework, businesses are classified based on expertise and autonomy, thereby providing a comprehensive overview. Type I businesses encompass daycare centers with distinct revenue structures regulated by the “Early Childhood Education and Care Act.” Type II businesses include General Meal Service and General Transportation, which operate autonomously without budget support. Type III businesses, which comprise Social Welfare, Call Centers, and others, typically receive budget support and range in expertise from low to moderate. Lastly, Type IV businesses include Education, Health Care, and Technology, and they receive budget support while having moderate to high expertise requirements. However, it is difficult to draw definitive conclusions due to the issues involved in precise segmentation of expertise and the division of “budget-supported to autonomous”. The results of this analysis are expected to aid stakeholders in resource allocation strategies, ultimately allowing those within diverse business classifications to optimize their workforce management.

Entrepreneurship in the sharing economy: A review of business models and social impacts

The emergence of the sharing economy has fundamentally transformed conventional company structures, presenting novel prospects for entrepreneurs and questioning existing conventions across diverse industries. This study offers an extensive examination of entrepreneurship within the sharing economy, delving into various company models and scrutinising its societal ramifications. The sharing economy, which involves peer-to-peer transactions mediated by internet platforms, has seen the rise of new entrepreneurial businesses. This paper explores the diverse and complex nature of sharing economy business models, encompassing various platforms such as ride-sharing, accommodation-sharing, asset-sharing, and skill-sharing. A thorough examination of each model to explore the fundamental concepts, operational processes, and crucial aspects that contribute to entrepreneurial success in this rapidly changing environment is being explored. This study examines the impact of different business models on consumer behaviour, market dynamics, and social developments. The assessment examines the good and negative outcomes, taking into account factors such as improved efficiency in resource utilization, economic empowerment of individuals, and potential difficulties linked to regulatory issues, labor rights, and market competitiveness. This paper focuses on the essential role of technology and digital platforms in promoting entrepreneurship within the sharing economy. Through an analysis of the impact of digitalization on market accessibility, trust mechanisms, and scalability, the role of technology as a driver for entrepreneurial innovation and expansion is emphasized. Additionally, it analyses the impact of regulatory frameworks on entrepreneurial activity, investigating the difficult balance between stimulating innovation and maintaining consumer protection, fair competition, and social equality. In conclusion, this research gives useful insights into the entrepreneurial environment of the sharing economy, presenting a comprehensive knowledge of diverse business models and their societal implications. By putting light on both opportunities and problems, thereby contributing to the current conversation on the role of entrepreneurship in determining the future of the sharing economy and its consequences for society at large.

The rise and transformation of big business in Argentina (1913–1971)

AbstractThis article analyses the structure and changes of large companies based on a new database of the 200 largest non-financial firms operating from 1913 to 1971 in Argentina. The main contribution of the research consists of the elaboration of the rankings of the 200 largest companies according to their paid-up capital between 1913 and 1971 and the construction of a database of large companies based on homogeneous sources and criteria. The study identifies the long-lasting presence of family-based diversified business groups and foreign multinationals from the first global period to the end of Import Substitution Industrialisation. It also shows that the presence of foreign companies among the 200 largest firms is higher than that identified in other countries. The study constitutes the first comprehensive research into big business in Argentina until the 1970s and a first attempt to identify the life cycles of the largest companies in Argentina.

Catalyzing Change: Unleashing the Power of Artificial Intelligence in Indonesian Business

Artificial Intelligence (AI) has become a transformative force in the modern business world. This research analyzes the impact of AI adoption in businesses, focusing on the Indonesian business context. We combine literature analysis, cross-sector case studies, and interviews with business stakeholders. The research findings indicate that AI has shifted the business paradigm in Indonesia by enhancing operational efficiency, altering traditional business models, and supporting better decision-making. Challenges related to algorithmic bias and AI ethics are also identified. The implications of this research include the need for thoughtful management of AI adoption, collaboration with regulators, and increased education and awareness regarding social impact and ethics. Further research can deepen the understanding of AI's impact in diverse business contexts in Indonesia. This research provides a solid foundation for understanding AI's role in modern business, bridging the global and local dimensions to detail the impacts, challenges, and opportunities faced by organizations adopting this technology.

Perlmutter visited. Japanese international business strategic orientation transformation in India: progress made and forces against

PurposeAlthough Asia's rise in the global economy is increasingly recognized, international business (IB) interactions between Japan and India remain under-commented. These interactions are especially salient due to the United Nations Sustainable Development Goal 17 (UN SDG 17), which focuses on partnerships. This study updates and analyzes the strategic orientation of Japanese multinational enterprises (MNEs) in India.Design/methodology/approachFollowing a subjectivist approach, this study employs a constructivist epistemology. Utilizing mixed methods, it obtains primary data from interviews and informal conversations with senior personnel from Japan and India and secondary data from archives. These data then undergo manual organic thematic analysis.FindingsThe study reveals instances of Japanese MNEs diverging from traditional ethnocentric orientations, such as senior management's growing commitment to India. The findings also indicate that the transformation to a polycentric orientation remains incomplete.Practical implicationsThe study uncovers themes impeding a polycentric transformation, offering insights for strengthening international partnerships and emphasizing the necessity of prioritizing local demands and cultural expectations.Social implicationsClues to strengthening IB contribute to attain UN SDG 17, especially given the advanced-emerging characteristics of the Japan–India dyad.Originality/valueThis study’s research makes a novel contribution to the literature on international strategic orientations by providing insights into a rare dyad – namely, Japanese MNE expansion in India. It is also a valuable and timely addition consistent with current beyond-China business diversification trends.

Research on Low-Density Parity-Check Decoding Algorithm for Reliable Transmission in Satellite Communications

Satellite communications face difficulties such as intensified environmental attenuation, dynamic time-varying links, and diverse business scenarios, which usually require channel coding schemes with high coding gain and high throughput. Low-density parity-check (LDPC) codes are dominant in satellite communication coding schemes due to their excellent performance in approaching the Shannon limit and the characteristics of parallel computing. The traditional weighted-Algorithm B decoding algorithm ignores the channel received information and involves frequent multiplication operations and iteration, which introduces the channel received information for hard-decision and constellation mapping processing. Meanwhile, we design the correlated reliability between the extrinsic information and the mapping processing information to improve the correctness of decoding. The multiplication operation in the iterative process can be replaced by the simple sum of the Hamming distance coefficient, the correlated reliability between the extrinsic information and the mapping processing information, and the extrinsic information frequency, thereby reducing the complexity and storage load of the system. The simulation results show that the presented MRAI-LDPC algorithm can obtain about 0.4 dB performance gain, and the average number of iterations is reduced by 68% under a low SNR. The algorithm can achieve better error-correcting performance and higher throughput, providing strong support for reliable transmission of satellite communications.

SLA-ORECS: an SLA-oriented framework for reallocating resources in edge-cloud systems

The emergence of the Fifth Generation (5G) era has ushered in a new era of diverse business scenarios, primarily characterized by data-intensive and latency-sensitive applications. Edge computing technology integrates the information services environment with cloud computing capabilities at the edge of the network. However, the evolving landscape of business models necessitates a unified edge architecture capable of accommodating diverse requirements, posing substantial challenges for service providers in meeting Service-Level Agreements (SLAs).In response to these challenges, we introduce SLA-ORECS. This innovative framework dynamically allocates dedicated and shared resources within the edge-cloud system to cater to service requests with varying SLAs, thereby facilitating performance isolation. Furthermore, we have developed an optimization algorithm to enhance the efficiency of SLA assurance during request dispatch.The evaluation of SLA-ORECS highlights its noteworthy performance improvements, particularly in terms of system throughput and average time consumption.

Customer churn prediction in imbalanced datasets with resampling methods: A comparative study

Customer churn presents a significant challenge for businesses in the era of subscription-based services because retaining customers plays a key role in sustained growth. Existing techniques for automatic churn prediction suffer from a primary challenge inherent in datasets as their significant disproportion between majority and minority classes, which may result in model bias favoring the dominant class. This study presents a comprehensive analysis of Customer Churn Prediction (CCP) with a focus on three public highly imbalanced datasets. The explored datasets span diverse business sectors, including telecommunications, online retail, and banking. We employ a comparative analysis regarding fourteen distinct classification methods considering popular resampling strategies, namely the Synthetic Minority Over-sampling Technique (SMOTE) and the Adaptive Synthetic Sampling (ADASYN). In particular, we investigate a specific configuration that combines a novel two-phase resampling method predicated on both clustering and ensemble techniques in conjunction with Long Short-Term Memory (LSTM) networks. Our findings demonstrate competitive effectiveness, underscoring its potential for effective imbalance correction by further enhancing prediction accuracy. Achieved results suggest that in almost all instances, the integrated approach outperforms the standalone methods across different scenarios in the three datasets, particularly in terms of the Area Under the Curve (AUC). This research represents a significant contribution to the field of churn prediction for addressing class imbalance.

ASSISTANCE IN THE DEVELOPMENT OF BUSINESS DIVERSIFICATION TO OPTIMIZE INCOME FOR WOMEN'S COOPERATIVES IN BLITAR DISTRICT

The presence of Women's Cooperatives in Indonesia holds significant importance, despite the limited number of large-scale Women's Cooperatives. These cooperatives play a crucial role in supporting the government's efforts to address national challenges such as unemployment reduction, enhanced health outcomes, improved education, and the resolution of gender-related issues. Analysis of the objectives of this initiative reveals two primary issues: 1) Women's Cooperatives heavily rely on savings and loan business units, leading to elevated levels of bad credit in the women's cooperatives of Blitar Regency; 2) Administrators of women's cooperatives struggle to diversify their businesses beyond savings and loans. The initiative commences with preliminary activities, involving a literature review followed by field research utilizing secondary data. Subsequently, a focus group discussion (FGD) is conducted to assess the actual conditions of women's cooperatives in the field, engaging with the Cooperatives and Small and Medium Enterprises (UMKM) Department. Through mentoring endeavors, the aim is to reinforce cooperative management, enabling the development of diversified business ventures beyond savings and loans. This is to be achieved through improved financial planning and activities. Additionally, the initiative aspires to instill in management a comprehensive understanding of business risk management.

Household resilience of women migrant worker sellers of Jamu Gendong

Background The selling of Jamu Gendong (an Indonesian traditional herbal medicine), is closely associated with the informal work of women who migrate to different regions. In Sukoharjo Regency and Wonogiri Regency, Central Java Province, the pressing need to meet household necessities in their places of origin compels women to assume the role of breadwinners. Therefore, this research aimed to identify the livelihood capital and resilience of migrant women selling jamu gendong. Methods The study was conducted in Ciamis Regency, West Java Province, Indonesia, in November 2022, using quantitative and qualitative methods. Primary data were collected through structured questionnaires and in-depth interviews. The sample comprised 51 women selected through snowball sampling and actively involved in selling Jamu Gendong, along with six key individuals from relevant agencies. Results The results showed that the households of migrant women selling jamu gendong survived and adapted to the migration destinations to prevent poverty. This was attributed to the livelihood strategy of business diversification. In this context, migration was exclusively practiced by women without family members who rented accommodation together. This research identified different forms of capital these women possess, including their productive age and skills in preparing jamu gendong, physical capital encompassing road infrastructure, marketplaces, access to health and education facilities, and natural, social, and financial capital. Conclusions The findings contribute to a comprehensive understanding of the resilience demonstrated by migrant women selling jamu gendong. However, further research should be conducted in areas beyond the city center to obtain a holistic view of their resilience.

Research of Golden Investment Opportunity of the Blue-Chip Dividend King

Johnson & Johnson (JNJ) stands as a titan in the healthcare conglomerate sector, having long played a significant role in the global market. This paper undertakes a literature review methodology to delve deeply into JNJ's historical context, diverse business arms, and financial prowess. A Discounted Cash Flow (DCF) and comparative valuation method are applied to assess JNJ's investment potential, supported by a rigorous risk evaluation encompassing various facets from market dynamics to legal challenges. Concurrently, the study gauges the alignment of JNJ's strategies with prevailing pharmaceutical and healthcare trends. Conclusively, the analysis suggests tailored investment recommendations, encapsulating both immediate and future outlooks. The primary objective is to furnish prospective investors with a well-rounded assessment of JNJ's investment promise.

China's National Team: A Game Changer in Stock Market Stabilization?

This study investigates the influence of China's national team investors on stock market volatility and crash risks using 2011-2018 data. Findings show increased stock return volatility and decreased crash risks post-2015. The national team reduced risk for pledged shares, while treatment firms reduced R&D investment and diversified business more than control groups. A difference-in-difference approach reveals heightened volatility in firms with national team ownership after 2015, questioning the efficacy of these interventions. This research offers insights into government intervention in financial markets, emphasizing the national team's impact on market stability and economic outcomes.