Improve Business Outcomes Research Articles

Environmental management and its effect on innovation and export performance: Empirical research in Chinese manufacturing companies

This study investigates the role of Chinese manufacturing firms in implementing Environmental Management Systems (EMS) to understand how these practices impact export performance and the mediating and moderating effects of innovation. Using structural equation modeling on data from 226 Chinese manufacturing businesses, our findings indicate that EMS indirectly enhances export performance through innovation. This research provides significant contributions to general management by integrating EMS and innovation within the strategic framework of manufacturing firms, offering insights for enhancing competitive advantage and sustainability in global markets. The findings also present practical implications for managers to leverage EMS and innovation for improved business outcomes and sustainable practices.

Antecedents of Startup Company Performance in Indonesia: A Pathway Towards Achieving Sustainable Development Goals

Objective: This study examines CEO competency's impact on business performance in startup companies, particularly in Indonesia. It also explores the mediating role of business networks in this relationship. Theoretical Framework: The study builds on theories of leadership competency and network theory to investigate how the competencies of startup CEOs influence both business performance directly and indirectly through the development of business networks. Method: The study employs Structural Equation Modeling-Partial Least Squares (SEM PLS) to analyse data collected from 300 respondents drawn from a population of 2,419 startup companies in Indonesia. Results and Discussion: The findings reveal that CEO competency significantly positively affects both business performance and the establishment of business networks. Furthermore, business networks also positively influence business performance. The study confirms that business networks serve as a crucial mediating factor in the relationship between CEO competency and business performance, strengthening the overall performance of startup companies. Research Implications: These results offer practical insights for startup CEOs, suggesting that enhancing leadership competencies and fostering business networks can significantly improve business outcomes. The findings also contribute to the broader understanding of how leadership skills in startups can mitigate the high failure rates in this sector. Originality/Value: This research is the first to empirically investigate the role of CEO competency in startup business performance in Indonesia, specifically focusing on the mediating role of business networks. Its novelty lies in addressing startups' high failure rates through the lens of leadership and networking.

Closing the referral loop on health-related social needs.

184 Background: Additional clinical challenges arise by way of health-related social needs (HRSNs) presenting barriers outside of clinic walls. Taking a person-centered approach by assessing and addressing HRSNs to overcome barriers can be practiced through resource referrals to community-based organizations offering specialized social services. Using closed-loop referral (CLR) technology, HRSNs can be addressed resulting in higher treatment completion rates and on-time visits contributing to positive health outcomes, quality of life, and improved business outcomes. HRSNs are categorized in major groups such as transit, food, housing, money, health (i.e. mental health, dental care, nutrition counseling, etc.), and care (i.e. daycare, end-of-life care, physical safety, etc.). In this study, we seek to substantiate CLR technology to address common HRSNs impacting cancer patients through real-time data sharing and resource facilitation showing reportable evidence that the HRSNs have been addressed. Methods: On June 5 th , 2023, The US Oncology Network (The Network) launched Findhelp’s CLR platform onboarding users in over 600 clinical service sites nationwide. Implementation and change management began with a pilot group and deployment to remaining clinical sites in a sequence of three waves. Methods used to measure engagement came through onboarding analytics and click rates tracked through the Findhelp CLR platform. For training and support job aides, new user workflows, promo materials and weekly office hours were held to catalyze engagement. Results: Within an eleven-month measurement period, 75% of practices in The Network showed navigation activities within the referral platform. The top five resource searches by need included health (21.7%), transit (20.8%), food (19.9%), housing (18.9%), and care (6.5%). Over 2,000 referrals were made with 1,306 being CLRs for nearly 500 patients receiving help to meet identified HRSNs through the CLR technology. Conclusions: In this study, over 50% of patients referred to social care services were captured as successfully receiving help meeting identified HRSNs. This study opens doors to further research on what HRSNs were not met, and to identify distressed demographics by location and geographical resource deserts with unmet HRSNs.

A Comprehensive Study on Decision-Making Algorithms in Retail and Project Management using Double Framed Hypersoft Sets

In today's dynamic business environment, effective decision-making plays a crucial role in the success of retail businesses and project management endeavors. This paper presents a comprehensive study of decision-making algorithms, focusing on the utilization of Double Framed Hypersoft Sets (DFHS) in retail and project management contexts. The study explores the theoretical foundations of DFHS and its practical applications in customer segmentation, personalized marketing, project selection, and resource allocation. Various algorithms and methodologies incorporating DFHS are discussed and analyzed, highlighting their advantages, limitations, and real-world implications. Through a series of numerical examples, case studies, and comparative analyses, this study provides valuable insights into the role of DFHS in optimizing decision processes, improving business outcomes, and fostering innovation in retail and project management domains.

Bridging the gap between IT and OT to improve industrial cyber security

Understanding cyber security risks is important for everyone. In this paper you will gain perspective on the cyber security challenges facing organisations today that operate within manufacturing and critical infrastructure industries, across their information technology (IT) and operational technology (OT) teams. You will also gain insight into potential solutions. IT teams have evolved distinctly, prioritising data security, access controls and system hardening in networked computing environments. OT teams manage and operate industrial control system (ICS) equipment with specific requirements around reliability and uptime for the purpose of ensuring physical outcomes in manufacturing or critical infrastructure production environments. IT and OT have traditionally operated separately within organisations because they serve different functions. The lack of interaction and understanding between IT and OT has led to cyber security vulnerabilities and frustration between organisations. IT may want to patch OT systems but get pushback because downtime halts production. OT may distrust IT recommendations because they have historically caused operational disruptions. This tension has caused many organisations to avoid trying to connect these two worlds; however, as digital transformation and Industry 4.0 initiatives bring IT and OT systems together, new cyber risks emerge. Industrial Internet of Things (IIoT) devices, legacy equipment, unpatched programmable logic controllers (PLCs) and obscured asset inventories create vulnerabilities. Despite their differing perspectives and priorities, however, collaboration between IT and OT is essential to secure today’s converged environments. Discover proven steps that can be taken to bridge the gaps between organisations to provide greater security across the enterprise, while strengthening internal teams and improving business outcomes.

Digital Marketing Dynamics: Investigating Influential Factors in Consumer Purchase Behaviour

In today’s digital age, digital marketing has become an integral part of our daily lives. The internet, mobile applications, social media and other digital communication tools have become ubiquitous and are used by billions of people worldwide. This study aimed to investigate the factors that affect consumer purchase decisions in digital marketing. A set of self-administered questionnaires has been distributed to 166 respondents in Malaysia. The stimulus-organism-response (SOR) theory was employed in this study. The independent variables included in this study are email marketing, social media marketing, mobile marketing, online advertising, influencer marketing and trust plays as a moderating variable in the study. The findings of this study revealed that five out of eleven hypotheses were supported. Trust significantly showed a mediation effect on the relationship between mobile advertising and online advertising on purchase decisions. These findings contribute to Sustainable Development Goal 9 (Industry, Innovation, and Infrastructure) by providing inputs on digital marketing’s effects, which can relate to the advancements in technology and innovation within the marketing sector. This research offers important insights for individuals, marketers and employers. Digital marketing is a powerful tool that can help businesses reach a larger audience, even with a limited budget. Utilising digital marketing tools like online advertising provides a valuable opportunity to strengthen online visibility, target the right audience, boost exposure and improve business outcomes.

Integrating behavioral science into operational risk management: A new paradigm for the FMCG sector

This paper explores the rationale for integrating behavioral science into ORM within the FMCG sector, examines key behavioral principles relevant to risk management, and proposes practical frameworks for implementation. By adopting this new paradigm, FMCG companies can enhance their resilience, adaptability, and overall performance in an increasingly complex and dynamic business environment. Operational risk management (ORM) is paramount for ensuring the stability and success of businesses, particularly in fast-moving consumer goods (FMCG) sectors where operational disruptions can lead to significant repercussions. However, traditional ORM approaches often overlook the human element, focusing solely on systems, processes, and external factors. This paper advocates for the integration of behavioral science into ORM, recognizing the pivotal role of human behavior in shaping operational risks and offering strategies to effectively mitigate these risks. The rationale for integrating behavioral science into ORM within the FMCG sector is explored, emphasizing the need to understand and influence human behavior to enhance resilience and adaptability. Key behavioral principles relevant to risk management are examined, including decision-making biases, social dynamics, and cognitive heuristics. These insights provide a foundation for developing practical frameworks for implementation, encompassing areas such as demand forecasting, compliance, and employee engagement. By adopting this new paradigm, FMCG companies can enhance their resilience, adaptability, and overall performance in an increasingly complex and dynamic business environment. Integrating behavioral science into ORM enables companies to anticipate and address human factors that contribute to operational risks, leading to more effective risk management strategies and improved business outcomes .In conclusion, the integration of behavioral science into ORM represents a paradigm shift that recognizes the importance of understanding and influencing human behavior in mitigating operational risks. By incorporating behavioral insights into their risk management practices, FMCG companies can better navigate challenges, capitalize on opportunities, and ultimately, achieve sustained success in today's competitive marketplace.

Integrating Azure Services for Real Time Data Analytics and Big Data Processing

Integrating Azure services for real-time data analytics and big data processing is a transformative approach that leverages the power of cloud computing to handle vast amounts of data at scale. Azure offers a wide array of services such as Azure Synapse Analytics, Azure Data Lake, Azure Stream Analytics, and Azure Databricks, which together enable businesses to extract valuable insights from both structured and unstructured data in real time. These services provide seamless integration, allowing for real-time data ingestion, transformation, and analysis, facilitating quicker decision-making processes. Azure’s capabilities in big data processing allow for scalable and efficient storage of data, ensuring optimal performance even as data volumes grow. By utilizing tools like Azure Data Factory and Azure HDInsight, organizations can automate complex workflows and apply machine learning algorithms for predictive analytics, driving innovation and competitive advantage. The integration of Azure's real-time analytics services also supports the use of advanced technologies like artificial intelligence (AI) and Internet of Things (IoT), enabling companies to monitor live streams of data from various devices and platforms. This infrastructure not only enhances operational efficiency but also ensures a more proactive approach to problem-solving by identifying trends and anomalies as they occur. In conclusion, Azure’s comprehensive suite of services offers a robust platform for managing and analysing big data in real time, empowering organizations to leverage data for better decision-making and improved business outcomes.

Impact of Data Analytics Capabilities on CRM Systems’ Effectiveness and Business Profitability

In the current digital era, understanding the role of Data Analytics Capabilities (DAC) in Customer Relationship Management (CRM) systems is essential for businesses seeking better decision-making. While DAC is acknowledged as a Critical Success Factor (CSF) for CRM systems, there is a gap in empirical evidence quantifying its effect on business profitability. This study aims to (1) present the conceptual foundation of the impact of DAC for CRM systems on marketing decisions and business profitability, and (2) empirically estimate the impact of integrating DAC on marketing performance and business profitability. Focusing on the retail sector, the study gathered 131 questionnaires from employees involved in CRM and DAC in Lebanon, and used the SPSS tool for data analysis. The research findings provide advanced empirical evidence of the importance of DAC as a CSF for CRM systems, alongside people, process, and technology dimensions. Results show that the integration of DAC represents a significant step forward in enhancing the effectiveness of CRM systems and achieving better business profitability. This study challenges the conventional understanding of technology's role in improving business outcomes, thus providing valuable theoretical and practical implications for organizations aiming to enhance their CRM systems.

Total Quality Management Practices and Performance of East African Breweries Limited, Kenya

Total quality management (TQM) is a continuous process that seeks to point out and eradicate managerial gaps in organizations. It also aligns organizational management, enhances good customer service and empowers the training of employees. TQM uses strategies, data and communication channels to bring together the required quality principles into the organization’s activities and culture. This study examined the relationship between Total Quality Management practices and organizational performance at East African Breweries Limited (EABL) Kenya. The study sought to establish the effect of customer focus on the performance of EABL in Kenya. The research examined the effect of continuous quality improvement on the performance of EABL in Kenya. The study also assessed the effect of strategic approaches on the performance of EABL in Kenya. Contigency thory,Service quality theory, Sigma six quality improvement theoryand system theory of management were reviewed concerning the four variables involved in this study to analyze the gaps that lead to further research. The population target was 60 EABL managers in the departments directly related to TQM practices. Since the population was moderate, there was no sampling. Instead, census method was used and therefore the entire population was included in this study. The study used an explanatory research design where questionnaires were used as a data collection instrument. Descriptive statistics was used to analyze data in tables and charts according to the research objectives. Quantitative statistic processes were also used to derive correlation and regression analysis to establish the extent and nature of the relationship between the independent variables and dependent variables. Construct validity showed a description of whether support is given by case studies concerning the interpretation of variables in the study. The findings of the study indicated a positive significance by benefiting East Africa Breweries Limited in understanding to what extent the total quality management practices impact the performance of the company. The findings demonstrate that East African Breweries Limited (EABL) exhibits a strong commitment to Total Quality Management practices and a customer-centric approach to quality, resulting in enhanced effectiveness, customer retention, and market advantage. EABL's focus on customer satisfaction, loyalty, and market performance highlights the strategic significance of TQM in the company's success and competitiveness. The study concludes that implementing TQM practices can lead to improved business outcomes, emphasizing the importance of effective TQM in achieving better organizational results and market success.

Proposing A Conceptual Model for Asnafpreneur Success: Social Networks and Resource Dependence in Low-Income Regions

This paper proposes a conceptual model integrating Social Network Theory (SNT) and Resource Dependence Theory (RDT) to examine the business performance of Asnafpreneurs—entrepreneurs from marginalized communities supported by zakat—in low-income regions. While Asnafpreneurs frequently rely on social networks to access resources, they face significant challenges, including limited network diversity and heavy dependency on external actors like zakat institutions for financial and operational support. The model presented in this study aims to demonstrate how optimizing social networks can help reduce resource dependency and improve business outcomes, such as revenue growth, sustainability, and entrepreneurial autonomy. To guide future empirical validation, the paper suggests a mixed-methods approach, combining qualitative insights from in-depth interviews with quantitative measures, including social network analysis and structural equation modeling, to test the proposed relationships. This approach provides a roadmap for assessing the impact of social networks on business performance and understanding the mediating role of resource dependency. The findings contribute to the theoretical development of SNT and RDT by extending their application to marginalized entrepreneurship within a faith-based context. The paper also offers practical implications for policymakers and zakat institutions, providing strategies for designing more effective entrepreneurial support programs aimed at empowering Asnafpreneurs in low-income communities.

Evaluating Service Quality and Business Outcomes Post-Pandemic: Perspective From Hotels in Emerging Market

The impact of the novel coronavirus has been severe, and while crises are impossible to predict, they must be anticipated and planned for in business. However, less is known about the preparedness of emerging markets, particularly in the hospitality industry in Nigeria. Therefore this study seeks to situate the service quality debate within the emerging hotel service arena by exploring service quality and business outcomes in selected hotels within the Ogun East senatorial district, Ogun State, Nigeria. The study adopted the survey research design, which is cross-sectional. A convenience sampling technique was adopted in arriving at the respondents. A total of 232 copies of a questionnaire were received from the customers of twenty hotels in six major towns within the Ogun East senatorial district -Ijebu-Ode, Ago-Iwoye, Ijebu-Igbo, Sagamu, Ilishan-Remo, and Iperu-Remo representing 89.3% response rate. The regression analysis was carried out to test the effect of service quality on business outcomes. The main findings of the empirical study show that there is strong support for service quality to improve business outcomes in hotels. Specifically, service quality significantly impacted both competitiveness and brand recognition, the study's two measures of business outcomes. However, taken individually, the study found that tangibility as a factor showed little impact on outcomes but a strong impact on brand recognition. Similarly, service assurance significantly affected business competitiveness but only mildly impacted brand recognition. The distinct effects of service quality and business outcomes post-pandemic in Nigeria were highlighted. It also provided hotel stakeholders and owner-managers with insights on the need to enshrine service quality management in the corporate policies to reduce customer dissatisfaction and poor business outcomes. It is also essential for hotel operators to stay abreast of the current and future needs of an ever-evolving industry and to meet the demands of guests who are becoming more sophisticated. Innovation and originality are essential to the hotel industry's outcome. This is one of the first studies to provide empirical evidence of the relationship between service quality and business outcomes post-pandemic in Nigeria. The results provide new insights into this relationship and may clarify divergent results found in the literature from other climes

Make Microfinance Great Again: Can Flexibility in Repayments Improve Business Outcomes in North India?

Classic microfinance loan contracts characterised by rigid weekly repayment schedules used by most microfinance institutions (MFIs) offer little flexibility—and little benefit—to borrowers who are poor and have seasonal income. Previous research has also shown that such contracts can negatively affect the economic well-being of poor borrowers leading to underinvestment of capital, selling of productive assets, over-indebtedness through cross-financing from informal sources, reductions in consumption and income, and in some cases, a deterioration in borrowersʼ mental health arising from stress and worry. If lenders offered more flexibility in loan repayment schedules, would it help to overcome some of these problems? To explore this, we tested whether clientsʼ business outcomes were sensitive to various repayment schedules using primary data collected from the clients of three MFIs, a cooperative society and a few local traders specialising in business lending in a village in North India. We analysed alternatives to the rigid contract model, focussing on the degree of flexibility and the length of gap between repayments in the loan schedule. This study finds that clients repaying their loans monthly invested more in their businesses and earned higher income, compared both to those who repaid weekly and to those with an irregular payment schedule. JEL Codes: G12, D12, O16, O12

Enhancing Cloud Resource Management Based on Intelligent System

Cloud computing is a significant technology model with the strongest potential to change the way IT activities are carried out. The cloud offers low-cost and scalable IT resources. Cloud providers strive to improve business outcomes so cloud systems become more complex. The intelligent cloud has a number of issues, including optimizing the cloud service and designing and distributing resources adaptively and economically. There is a rising trend toward adopting intelligent technologies to better cloud management in particular. This paper introduces an intelligent method to manage cloud resources without delay or trouble. Starting with designing a system based on a genetic algorithm (GA) as a computational tool to achieve the goal and plan a predictive request then depending on the round robin (RR) algorithm to allocate the requests for processing. To evaluate the performance of this method, the proposed algorithm was verified in 145 requests. Where the implementation system achieved a reasonable result.

Tech-Business Analytics in Secondary Industry Sector

Purpose: Businesses in all sectors, including the secondary industry, will turn to tech-business analytics as a crucial tool. Tech-Business Analytics' role in the secondary industrial sector is to support companies in making data-driven decisions that optimize their operations, boost productivity, and boost profitability. Businesses may optimize their supply chains by accessing data on suppliers, inventories, logistics, and other aspects to spot inefficiencies and areas for improvement. Organizations can use this information to reduce downtime and boost production to schedule maintenance in advance and predict when machinery and equipment will likely break. Examining data on product flaws, customer complaints, and other aspects can help firms improve their quality control systems by identifying root causes and implementing corrective measures. Studying data on consumer behaviour, industry trends, and other factors can help organizations optimize their sales and marketing activities and find chances for expansion and higher profitability. Design/Methodology/Approach: Businesses can use several processes in the tech-business analytics methodology to help them make decisions based on data in the secondary industry sector. This secondary industry sector can entail enhancing the effectiveness of the supply chain or decreasing equipment downtime. After identifying the issue, the necessary data must be gathered and prepared. Once the data is collected, it must be analyzed using statistical models and other analytical methods. This collected data might entail looking for relationships between multiple variables, spotting trends in consumer behaviour, or predicting outcomes using predictive models. Findings/Result: It is described in the article how tech-business analytics in the secondary industrial sector will have managed the growth itself from its inception to the present. The Tech-Business Analytics technique in the secondary industry sector offers a structured approach to problem-solving using data analysis to assist in better decision-making and improve business outcomes. Originality/Value: Exploring the evolutionary path of business analytics transforms into the advanced realm of technology-driven business analytics within the secondary industry sector. A generic architecture also examines 130 recently published Tech Business Analytics in Secondary Industry sector research projects for technical purposes. Tech-Business Analytics is a new field that applies ICCT-underpinning technologies in Tech-Business Analytics (TBA). TBA is intended to provide businesses with unprecedented opportunities for growth and innovation in secondary industry sectors. Paper Type: Exploratory research.

The Role of Intellectual Capital to Fill the Missing Link in The Relationship Between Social Responsibility and Islamic Banking Performance in Indonesia

The purpose of this research is to analyse how Islamic banks in Indonesia performance using antecedents of their level of social responsibility and intellectual capital. In addition, the mediating role of IC in the connection between CSR and firm performance is examined. This study predicts that CSR strategies have the potential to enhance corporate IC, giving rise to a new type of IC called "Sustainable IC," which is closely related to environmental and social knowledge that businesses must have in order to thrive in the modern business world. This study result’s confirmed the mediating role of IC in the connection between CSR and performance. This study's findings have important practical implications for banks, which may use them to justify spending more on CSR implementation techniques that boost CSR indicators linked to more extensive use of IC resources and, hence, improved business outcomes. The findings also support the positive impact of IC and social responsibility on the performance of Islamic banks in Indonesia, demonstrating the existence of a causal link between the two

Bringing advanced technology to strategic decision-making: The Decision Intelligence/Data Science (DI/DS) Integration framework

There is a widespread stated desire amongst both public and private organizations worldwide to engage in more significant “evidence-based reasoning” and to be more “data-driven.” We argue that these two goals are proxies for the often-unstated goal of improving the exploration of possible futures as foresights that could lead to better strategic decisions and improved business outcomes. From this perspective, data and analytics hold great promise and are necessary—but not sufficient—for improving strategic decision-making. Something more is needed to realize this potential. We specify how to fill this gap using an integration framework between technology and decision-makers, which is especially appropriate in complex and/or volatile environments. Our solution—which comprises a methodology as well as a software architecture—therefore unifies not only human decision makers to technology but each other and also integrates several disciplines that have been hitherto unnecessarily separated. Thereby, it could help organizations to address increasing challenges better as well as improve the exploration of possible futures.

Workplace Inclusivity: A Literature Review From a Strategy-As-Practice Perspective

Inclusive work environments are more likely to attract and retain a diverse talent pool, improving business outcomes and competitive advantage. However, inclusivity has been treated as a sum of organizational behaviour norms elaborated by savvy organizations. In line with real-world practices, we advance that inclusivity is a strategic practice that emerges as an inter-related and co-evolving pool of influences from the individual, firm, and environment, elevating it as a strategic management topic. We implemented a systematic literature review (SLR) of selected contributions dealing with the role of workplace inclusivity. Collected papers have been analysed by considering the so-called strategy-as-practice (s-as-p) perspective (i.e., the doing of strategy, who does it, what they do, how they do it, what they use, and what implications this has for shaping strategy), hence, enriching strategy theory, empirical research, and real-world practice. We offer a typology of strategic inclusivity practices that scholars and practitioners can use to study workplace inclusivity strategically. The proposed typology identifies the different domains of inclusivity by considering the level of praxis and practitioners. This article is the first to provide an in-depth and broad review of inclusivity in the workplace via a strategic management lens.

Contribution of Design Thinking to Leadership Outcome

Abstract This article explores the various types of leadership used in Lebanese small and medium-size enterprises (SME s). The purpose is to define the roots of the commercial leadership problems in Lebanon and to identify ways to improve business outcomes, taking as a reference point a human-centered management approach called Design Thinking (DT). The article investigates whether a DT approach can contribute to better leadership. An inductive qualitative approach has been used to conduct research into this question, with data collected by means of semi-structured interviews with Lebanese SME leaders. Content analysis and lexical and thematic approaches show that there are two dominant issues in Lebanese leadership: a complete denial of employees’ right to access decision making; and an incomplete human-centered management approach, one showing a lack of empathy and an absence of a performance evaluation process.

What (de) motivates customers to use AI-powered conversational agents for shopping? The extended behavioral reasoning perspective

Artificial Intelligence (AI)-powered conversational agents have become ubiquitous tools in the digital transformation of conventional customer-company interactions. Despite the widespread implementation of Artificial Intelligence (AI)-powered conversational agents, there is still a limited understanding of how customers use and resist these technologies for shopping. To address this gap, this study investigates factors that influence the usage and resistance of AI-based conversational agents for shopping using the extended behavioral reasoning theory (BRT) and partial least squares-based structural equation modeling (PLS-SEM). To test the proposed framework, this study conducted two empirical studies in South Korea. Study 1 focused on text-based chatbots with a sample of 232 participants, while Study 2 examined voice-based chatbots with a sample of 234 participants. The results of the both studies mainly supported the hypotheses driven by the extended BRT. Theoretically, this study contributes by offering a comprehensive understanding of customer motivation, attitudes, and behavioral intentions toward the use of AI-powered conversational agents in shopping. Managerially, this study provides important insights for retail managers and developers of AI-powered conversational agents for shopping. By understanding the factors that drive customer usage and resistance, managers, and developers can better design and deploy these innovative technologies to enhance the customer experience and improve business outcomes.