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This study compares the motives of holding cash between developed (Australian) and developing (Malaysian) financial markets.

For the period 2006–2020, the t-test, fixed-effect and generalised method of moment (GMM) model have been applied to a sample of 1878 (1,165 Australian and 713 Malaysian) firms.

The empirical results reveal that firms in developed financial markets hold higher cash compared to the developing financial markets. The findings confirm that motives to hold cash differ between developed and developing financial markets. The GMM findings further show that cash holdings (CH) in Australia are higher due to higher ratios of cash flow, research and development (R&D) and return on assets (ROA), and lower due to larger dividend payments. In the Malaysian market, however, cash flows and R&D are ineffectual, ROA falls and dividend payments rise CH.

The study helps managers, practitioners and investors understand that firms' distinct economic, institutional, accounting and financial environments are important. To attain the desired outcomes, they must thus comprehend and consider these considerations while developing suitable liquidity strategies.

To the authors' best knowledge, this is the initial research demonstrating how varied cash motives and their ramifications are in developed and developing financial markets. Therefore, this study identifies the importance that CH motives varied among financial markets and that findings from a particular market cannot be generalised to other markets because of the market and financial structural variations.

This study investigates the impact of US dollar volatility and oil rents on the performance of small and medium-sized enterprises (SMEs) in the Gulf Cooperation Council (GCC) region, with an emphasis on understanding how these factors influence SME financing constraints in economies with fixed currency regimes.

Employing a random effects panel regression analysis, this research considers US dollar volatility and oil rents as independent variables, with SME performance, measured through the financing gap, as the dependent variable. Controls such as trade balance, inflation deltas and gross domestic product (GDP) growth are included to isolate their effects on SME financing constraints.

The study reveals a significant positive relationship between dollar volatility and the financing gap, suggesting that increased volatility can exacerbate SME financing constraints. Conversely, oil rents did not show a significant direct influence on SME performance. The trade balance and inflation deltas were found to have significant effects, highlighting the multifaceted nature of economic variables affecting SMEs.

The study acknowledges potential biases due to omitted variables and the limitations inherent in the use of secondary data.

Findings offer pertinent guidance for SMEs and policymakers in the GCC region seeking to develop strategies that mitigate the impact of currency volatility and support SME financing.

The research provides new insights into the dynamics of SME performance within fixed currency regimes, which significantly contributes to the limited literature in this area. The paper further underscores the complex connections between global economic factors and SME financial health.

The primary objectives of the case study are to get the participants exposed to the issues of working capital which even profitable companies face on a day-to-day basis; give the participants an understanding of how to balance the, at times, conflicting objectives of increasing profits and sales through favorable credit terms; and expose them to the impact of increase in inventory levels and average collection period on margins in a period of slow growth. They will also learn about the concept of factoring and its uses.

The case study is about a group of companies engaged in education, steel fabrication and oil businesses owned by a single proprietor. The company was based in Fatehnagar which was part of Hyderabad district in the state of Telangana, India, and the case study traces the origins of the group from 1960s to 2021. The group was invested the surplus cash flows from the oil business to initiate and expand other businesses during this period. The economic downturn due to the COVID-19 pandemic had hit the company, particularly its oldest business – Noble Chemical Agency. The oil business was facing issues related to its growth and profitability, and the uncertainty around COVID-19-related restrictions had only augmented the fears of the management. The case study looks at issues and the dilemma which the owner of the company faced. The case study highlights various issues related to working capital management, especially related to receivables management and inventory levels faced by businesses during the slow-growth phase. It demonstrates how working capital management issues, if not resolved in time, can lead to insolvency of even a successful company with a sound business model.

The case study is meant for teaching in postgraduate management programs (Master of Business Administration and Postgraduate Diploma in Management) in the following courses: corporate finance/financial management course in the first year (the case study should be taught towards the end of the course); and management accounting courses in first year (the case study should be positioned in the middle of these courses). The case study can also be used to highlight issues related to working capital and small business management in a Management Development Programme (MDP) course for “Finance fundamentals for non-finance executives”.

Teaching notes are available for educators only.

CSS 1: Accounting and finance.

After completion of the case study, the participants would be able to understand the challenges in building a sustainable homestay tourism business; develop a positioning statement for La Pinekonez which builds a unique competitive advantage; and outline elements of the business strategy to profitably sustain and grow a sustainable tourism homestay in terms of service offering, pricing, marketing and operations.

La Pinekonez Homestay, located in the beautiful region of Himachal Pradesh, India, is the subject of this case study, which explores both its successes and its difficulties. In August 2022, Arvind, the dedicated sole proprietor of La Pinekonez, grappled with multifaceted challenges, the first being the foray of established hotel chains into the homestay business. As the protagonist, was is in dilemma of preserving La Pinekonez’s unique identity amidst corporate competitors, particularly with regards to differentiating from the expanding hotel chains. The clash between customer expectations for hotel-like amenities and the homestay’s commitment to sustainable tourism presented a crucial challenge. Negative reviews questioning the authenticity of La Pinekonez’s green initiatives heightened the complexity. Adding to Arvind’s predicament were the seasonal fluctuations in tourist inflow and his aspiration to embrace immersive tourism trends. This case study facilitates exploration of strategic positioning, sustainability management and marketing strategies in the dynamic and competitive hospitality industry. It also offers insights into the complexities of balancing differentiation, customer satisfaction and sustainability while navigating the evolving landscape of tourism trends.

This case study is suitable for students of tourism and hospitality management at postgraduate level. The case study can be discussed once the basic concepts of hospitality management and service dimensions are covered.

Teaching notes are available for educators only.

CCS 12: Tourism and hospitality.

This study aims to develop the alleviating bullwhip effects framework (ABEF) replenishment rules, and bullwhip, inventory fluctuations and customer service fulfilment rates were examined. In addition, automated smoothing and replenishment rules can alleviate supply chain bullwhip effects. This study aims to understand the current artificial intelligence (AI) implementation practice in alleviating bullwhip effects in supply chain management. This study aimed to develop a system for writing reviews using a systematic approach.

The methodology for the present study consists of three parts: Part 1 deals with the systematic review process. In Part 2, the study applies social network analysis (SNA) to the fourth phase of the systematic review process. In Part 3, the author discusses developing research clusters to analyse the research state more granularly. Systematic literature reviews synthesize scientific evidence through repeatable, transparent and rigorous procedures. By using this approach, you can better interpret and understand the data. The author used two databases (EBSCO and World of Science) for unbiased analysis. In addition, systematic reviews follow preferred reporting items for systematic reviews and meta-analyses.

The study uses UCINET6 software to analyse the data. The study found that specific topics received high centrality (more attention) from scholars when it came to the study topic. Contrary to this, others experienced low centrality scores when using NETDRAW visualization graphs and dynamic capability clusters. Comprehensive analyses are used for the study’s comparison of clusters.

This study used a journal publication as the only source of information. Peer-reviewed journal papers were eliminated for their lack of rigorousness in evaluating the state of practice. This paper discusses the bullwhip effect of digital technology on supply chain management. Considering the increasing use of “AI” in their publications, other publications dealing with sensor integration could also have been excluded. To discuss the top five and bottom five topics, the author used magazines and tables.

The study explores the practical implications of smoothing the bullwhip effect through AI systems, collaboration, leadership and digital skills. Artificial intelligence is rapidly becoming a preferred tool in the supply chain, so management must understand the opportunities and challenges associated with its implementation. Furthermore, managers should consider how AI can influence supply chain collaboration concerning trust and forecasting to smooth the bullwhip effect.

Digital leadership and addressing the digital skills gap are also essential for the success of AI systems. According to the framework, it is necessary to balance AI performance and accountability. As a result of the framework and structured management approach, the author can examine the implications of AI along the supply chain.

The study uses a systematic literature review based on SNA to analyse how AI can alleviate the bullwhip effects of supply chain disruption and identify the focused and the most important AI topics related to the bullwhip phenomena. SNA uses qualitative and quantitative methodologies to identify research trends, strengths, gaps and future directions for research. Salient topics for reviewing papers were identified. Centrality metrics were used to analyse the contemporary topic’s importance, including degree, betweenness and eigenvector centrality. ABEF is presented in the study.

This chapter aims to discuss the challenges facing these countries building productive capacity for development. This chapter makes use of data published by international organizations as indicators for measuring the state of development in the Arab region. Several indicators are presented to compare Arab countries with other world regions. The use of data identifies some of the gaps that countries in the Arab region need to close to strengthen capacity building for development and fostering economic growth. The findings from the data presented reveal that the productive structure in most Arab countries remains weak to generate production linkages and provide incentives for investment in nonenergy sectors. The failure of the export-led growth model to diversify output and promote development in energy producing countries has increased the dependence of these countries on global trade. Fluctuations in commodity prices and uncertainty about global demand for energy have influenced the ability of the state to construct strategies for rapid transformation. Except for the energy sector, the productivity of nonoil sectors remains low reflecting inadequate incentives and ineffective entrepreneurial capabilities. The study examines the challenges for building productive capacity in the Arab world. It illustrates the failure of the led-export model and its inability to prompted economic diversification, especially in the Gulf countries. The study contributes to the literature on capacity building in the Arab world so that to encourage researchers and students of development conducting studies concerning the main development challenges facing these countries.

The purpose of this study was to explore how transport companies in Uganda execute strategies in a turbulent business environment.

The study adopted an exploratory qualitative methodology using the data collected through an open-ended instrument. Utilizing the qualitative data analysis software QSR NVivo9, the data were analyzed following the Gioia's methodology. Verbatim texts were used to explain the emergent themes.

The study's findings show that to successfully execute strategies, companies in Uganda communicate, coordinate and put control systems in their operations. The activities undertaken include customer care, timely settlement of complaints, comfortable seats, playing local music, partnerships with reliable fuel stations, setting up strategic offices, cost management, use of experienced drivers, sub-renting vehicles and inspections.

The study produces a pioneering result of how transport companies execute strategies in a turbulent business environment, an aspect that has not been adequately highlighted in previous studies.

The current environment is unhelpful to female entrepreneurs, and they need to overcome numerous barriers when starting their own businesses. In this study, the researchers investigated the significant barriers that Pakistani female entrepreneurs require to overcome in this respect.

In this study, the researchers used a quantitative study and they used a questionnaire to survey the respondents and collect cross-sectional data. The researchers targeted female students who were undertaking bachelor’s and master’s degree programs in different Pakistani public and private sector universities. Accordingly, the researchers based this study’s findings on the usable samples received from 498 Pakistani female students.

The researchers used a structural equation model (SEM) in this study and its findings highlight that aversion to risk (ATR) has an insignificant impact on entrepreneurial inclinations (EI). In addition, fear of failure (FoF), lack of resources (LoR), aversion to hard work and stress (ASH) and the lack of social networking (LSN) have negative and insignificant effects on EI. The ATR factor has an insignificant effect on entrepreneurial success (ES), whereas FoF, LoR, ASH and LSN are negative and insignificant predictors of Pakistani female students’ ES.

This study’s findings may help Pakistani women to overcome the barriers to ES. In this respect, the researchers recommend that the Pakistan Government and policymakers develop significant strategies to provide the conducive business environment and to financially support Pakistani women to start their own businesses. Furthermore, this study’s findings contribute greatly to the vast amount of current literature and help to overcome the entrepreneurial conditions and barriers that potential entrepreneurs from advanced and developing countries experience frequently.

This study’s findings provide empirical evidence of EI and ES in Pakistan.

Intellectual capital (IC) plays a crucial role in today’s volatile business landscape, yet its measurement remains complex. To better navigate these challenges, the authors propose the Integrated Intellectual Capital Measurement (IICM) model, an innovative, robust and comprehensive framework designed to capture IC amid business uncertainty. This study focuses on IC measurement models, typically reliant on secondary data, thus distinguishing it from conventional IC studies.

The authors conducted a systematic literature review (SLR) and bibliometric analysis across Web of Science, Scopus and EBSCO Business Source Ultimate in February 2023. This yielded 2,709 IC measurement studies, from which the authors selected 27 quantitative papers published from 1985 to 2023.

The analysis revealed no single, universally accepted approach for measuring IC, with company attributes such as size, industry and location significantly influencing IC measurement methods. A key finding is human capital’s critical yet underrepresented role in firm competitiveness, which the IICM model aims to elevate.

This is the first SLR focused on IC measurement amid business uncertainty, providing insights for better management and navigating turbulence. The authors envisage future research exploring the interplay between IC components, technology, innovation and network-building strategies for business resilience. Additionally, there is a need to understand better the IC’s impact on specific industries (automotive, transportation and hospitality), Social Development Goals and digital transformation performance.

This study aims to construct a sentiment series generation method for danmu comments based on deep learning, and explore the features of sentiment series after clustering.

This study consisted of two main parts: danmu comment sentiment series generation and clustering. In the first part, the authors proposed a sentiment classification model based on BERT fine-tuning to quantify danmu comment sentiment polarity. To smooth the sentiment series, they used methods, such as comprehensive weights. In the second part, the shaped-based distance (SBD)-K-shape method was used to cluster the actual collected data.

The filtered sentiment series or curves of the microfilms on the Bilibili website could be divided into four major categories. There is an apparently stable time interval for the first three types of sentiment curves, while the fourth type of sentiment curve shows a clear trend of fluctuation in general. In addition, it was found that “disputed points” or “highlights” are likely to appear at the beginning and the climax of films, resulting in significant changes in the sentiment curves. The clustering results show a significant difference in user participation, with the second type prevailing over others.

Their sentiment classification model based on BERT fine-tuning outperformed the traditional sentiment lexicon method, which provides a reference for using deep learning as well as transfer learning for danmu comment sentiment analysis. The BERT fine-tuning–SBD-K-shape algorithm can weaken the effect of non-regular noise and temporal phase shift of danmu text.