Search results

The study aims to evaluate the influence of capital structure decisions and asset structure on firms' performance for East African listed nonfinancial firms.

The research is descriptive and employs secondary data from the East African capital markets' websites. The generalized method of moments approach is used to estimate the relationship due to its ability to account for endogeneity problems.

The result shows that capital structure decisions and asset structure strongly influence the firms' performance. When long-term debts, short-term debts and tangible fixed assets increase, the return on total assets increases. An increase in the total debt ratio raises the return on equity (ROE). However, the increase in long-term debt lowers the ROE.

The results will help investors and potential investors decide on a financing policy that maximizes performance. Likewise, governments and other policymakers review the capital markets' frameworks to attract institutional and individual investors to the markets for financial availability and to increase profitability.

The research provides evidence on the influence of capital structure decisions and asset structure on firms' performance. Furthermore, its results contribute to firms' financing policy formulation and the corporate finance literature.

The empirical studies of the options market efficiency have reported contradictory results, which sometimes confuse practitioners and academicians. The aim of this study was to clarify several aspects of options market efficiency by exploring the answers to two main questions: Under what conditions is the options market more efficient? Are the discrepancies in the estimated efficiency due to the reality of efficiency or mismeasurement?

Using a meta-analysis approach, 54 studies have been analyzed, which included 1,315 tests. The sum of the observations for all of the tests is 3.7 m observation sets. The effect size (type r) has been used to compare the different statistics in different studies. The cumulative effect size and its diversification have been calculated by the random effects model and Q statistic, respectively.

The most interesting finding of the study was that the options market, in all circumstances, is significantly inefficient. Another important finding was that the heterogeneity of options market efficiency is due to the complexity of pricing relations, test time, violation index and price type. To overcome this heterogeneity and accuracy, future studies should test the no-arbitrage options pricing relations at different times and by different price types, using complex and simple pricing relations and either mean violation or violation ratio efficiency measures.

Public disagreement about the options market efficiency in past studies means that this variable is heterogeneous in different conditions. As a significant contribution, this study develops the literature by proposing the causes of options market efficiency heterogeneity.

This paper investigates the style timing and liquidity style timing vis-à-vis the market, size, value and momentum factors of the actively managed Indian equity mutual funds.

We examine the style timing of the funds using the augmented Carhart four-factor model by incorporating timing measures (Treynor and Mazuy; Henriksson and Merton). Based on this, the study explores the four-factor liquidity and volatility style timing exhibited by fund managers. The sample is from April 2000 to March 2018 and spans the volatile 2008 subprime economic crises. The sample comprised 182 actively managed equity funds from various sizes and was considered to be a well-diversified sample.

The results of our study provide strong evidence of market liquidity timing in India. No other style timing skills are observed in our analysis. Our results also imply that the fund managers might misidentify size timing as market timing if integrated liquidity timing measures are not employed, leading to false conclusions.

The findings of our study imply that the fund managers might misidentify size timing as market timing if integrated liquidity timing measures are not employed, leading to false conclusions.

This study, to our knowledge, is the first attempt to investigate the portfolio-based style timing in the Indian context.

The purpose of the study is to review and understand firm selection mechanism involved in government venture capital (GVC) funding and identify key factors influencing selection of tech-based firms for GVC funding.

This paper is based on real-time methodology. The data was generated from interviews of 60 young applicants, who applied for startup funding, and analyzed using statistical techniques to draw the results.

This review identifies financial viability, market viability and technological innovation to have the strongest predictive ability in firm selection process of the GVC funding program for tech-based youth-owned startups in the first round of interview. This review also highlighted that social impact is not a statistically significant variable in firm selection process in GVC funding.

This study tests the validity of the theory of GVC based on quantitative analysis of field data and identifies key factors with strong predictive abilities for GVC funding, more particularly for the youth-owned tech-based startups. This study brings to light the mechanism adopted for GVC funding and addresses gaps in the literature relevant to firm selection mechanism in GVC programs. This study would help GVC Fund Managers to review their own GVC programs in terms of selection mechanism and help them in appropriate designing of such programs.

Biculturals possess higher cultural intelligence than monocultural individuals. This study explores biculturals' key factors and attributes and how their cultural knowledge and identification influence International Business Negotiations (IBNs) and help their firms outperform others.

Data were collected from semi-structured interviews with 35 bicultural senior managers in Lebanon.

The findings highlight three essential qualities and behaviors that allow biculturals to act as a bridge between the parties during IBN: adaptability, cultural frame switching (CFS) and creativity.

This study explores the notion of bicultural personnel using their understanding of multiple cultures to be innovative, avoid groupthink and generate new creative ideas that help overcome stalemates during IBNs.

This study empirically aims to examine the collaboration between social enterprises (SEs) and impact investors (IIs), which are organisations with similar interests but with distinct logics, and in high demand in emerging economies with complex problems. Despite the significant economic contributions of these organisations, there have been limited studies examining how they collaborate in different contexts, including theoretical insights explaining how they gain partner fit from resource synergy.

Mainstream businesses use the compatibility and complementarity concepts to examine buyer–supplier strategic alliances. Using similar concepts in the context of hybrid organisations, the authors interviewed six pairs of SEs and IIs with dyadic relations in Nigeria, aiming to deeply understand how they align dissimilar logics in pursuing common goals in emerging economies.

The authors’ findings revealed how compatibility criteria from the institutional logics perspective and complementarity from social exchange theory guide collaboration between SEs and IIs in an emerging economy. Using these theories provides new insights that distinguish SEs and IIs collaboration from conventional theories on the internationalisation of businesses, which remained insufficient for understanding the cross-border operations of SEs.

The study holds practical implications for organisations, regardless of their size, international investors, governments, organisations and individuals desiring to pursue sustainable business agendas in emerging economies with huge impact opportunities and the process involved.

The outcomes of this study extend knowledge of the theoretical lens examining collaborative entrepreneurship from the perspective of hybrid organisations. It also challenged existing knowledge on collaboration between SEs and IIs, often characterised by potential tensions due to the dissimilarity of institutional logics of actors.

The cost of pharmaceutical supply chain due to drug waste is one of the current major issues in health care. Drug waste associated with intravenous (IV) fluid form of medication is one of the crucial issues for many pharmacies. The purpose of this paper is to apply a cross-docking model to minimize the IV delivery lead time to reduce drug waste by scheduling staff in a local hospital’s inpatient pharmacy.

A mixed integer linear programming model is applied to the IV delivery system of a hospital. The parameters are selected based on the observations made in the inpatient pharmacy.

The result implies that cross-docking approach can be effectively applied to IV delivery system. In fact, the cross-docking optimization model employed in this case study reduces the IV delivery completion time of the inpatient pharmacy by 41 percent.

The scope of this research is limited to the activities performed after IV preparation.

The application of cross-docking system in staff scheduling will be beneficial for health care organizations that aim to minimize medication waste.

The prime value of this study lies in the introduction of a cross-docking concept in an internal hospital ordering process. Cross-docking models are widely used in general supply chain systems; however, their application for specific activities inside hospitals is the novelty of this study, which can fill the research gap in terms of drug waste management within the inpatient pharmacy.

This study aims to explore the downstream pharmaceutical supply chain (PSC) and provides insight to the delivery process of medicines and associated operational inefficiencies.

An exploratory, qualitative approach was adopted to examine PSC inefficiency within two European contexts, namely, the UK and Greece. Data was gathered through interviews and a thematic analysis conducted to analyse the data and identify challenges faced by both supply chains(SCs).

The medicines delivery system needs to be enhanced in terms of quality, visibility, speed and cost to perform effectively. The findings demonstrated that although the healthcare SCs in the two European contexts have different operational structures, the results are in concordance with each other. Financial, communication, waste and complexity issues were the major concerns.

To the knowledge this is the first study to examine aspects of the medicines SC via a cross-case analysis in the UK and Greece and extends the body of knowledge. A broader sample of responses is warranted to further validate these findings.

The study outputs can inform pharmacies’ strategic to instigate targeted improvement interventions. The implications of which may be extrapolated further to other European healthcare organisations.

This research contributes to the academic literature by adding further theoretical insights to SC strategy development, especially those that have been characterised as highly complex. The study identifies four key areas of intervention needed within this SC (in both countries) to promote higher level efficiencies and effectiveness.

The purpose of this study is to extensively explore the vehicular network paradigm, challenges faced by them and provide a reasonable solution for securing these vulnerable networks. Vehicle-to-everything (V2X) communication has brought the long-anticipated goal of safe, convenient and sustainable transportation closer to reality. The connected vehicle (CV) paradigm is critical to the intelligent transportation systems vision. It imagines a society free of a troublesome transportation system burdened by gridlock, fatal accidents and a polluted environment. The authors cannot overstate the importance of CVs in solving long-standing mobility issues and making travel safer and more convenient. It is high time to explore vehicular networks in detail to suggest solutions to the challenges encountered by these highly dynamic networks.

This paper compiles research on various V2X topics, from a comprehensive overview of V2X networks to their unique characteristics and challenges. In doing so, the authors identify multiple issues encountered by V2X communication networks due to their open communication nature and high mobility, especially from a security perspective. Thus, this paper proposes a trust-based model to secure vehicular networks. The proposed approach uses the communicating nodes’ behavior to establish trustworthy relationships. The proposed model only allows trusted nodes to communicate among themselves while isolating malicious nodes to achieve secure communication.

Despite the benefits offered by V2X networks, they have associated challenges. As the number of CVs on the roads increase, so does the attack surface. Connected cars provide numerous safety-critical applications that, if compromised, can result in fatal consequences. While cryptographic mechanisms effectively prevent external attacks, various studies propose trust-based models to complement cryptographic solutions for dealing with internal attacks. While numerous trust-based models have been proposed, there is room for improvement in malicious node detection and complexity. Optimizing the number of nodes considered in trust calculation can reduce the complexity of state-of-the-art solutions. The theoretical analysis of the proposed model exhibits an improvement in trust calculation, better malicious node detection and fewer computations.

The proposed model is the first to add another dimension to trust calculation by incorporating opinions about recommender nodes. The added dimension improves the trust calculation resulting in better performance in thwarting attacks and enhancing security while also reducing the trust calculation complexity.

The goal of making buy-in decisions is to purchase materials at the right time with the required quantity and a minimum material cost (MC). To help achieve this goal, the purpose of this paper is to find a way of optimizing the buy-in decision with the consideration of flexible starting date of non-critical activities which makes daily demand adjustable.

First, a specific algorithm is developed to calculate a series of demand combinations modeling daily material demand for all the possible start dates. Second, future material prices are predicted by applying artificial neural network. Third, the demand combinations and predicted prices are used to generate an optimal buy-in decision.

By comparing MC in situation when non-critical activities always start at the earliest date to that in situations when the starting date is flexible, it is found that making material buy-in decision with the consideration of the flexibility usually helps reduce MC.

In this paper, a material buy-in decision-making method that accounts non-critical activities’ flexible starting date is proposed. A ternary cycle algorithm is developed to calculate demand combinations. The results that making material buy-in decision considering non-critical activities’ flexible starting date can reduce MC in most times indicates that contractors may consider non-critical activities’ flexibility a part of the buy-in decision-making process, so as to achieve an MC decrease and profit increase.