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The paper is devoted to modeling a pricing policy of competitive firms in a “closed” economy framework.

The proposed model can be regarded as an analog to CGE model and is based on the intersectoral balance methodology incorporating linear demand functions for goods and services.

By performing different model experiments, we show that a certain degree of competition can bring more profit to all competing firms, than in case of complete absence of such competition, what is also supported by empirical investigation. This finding implies that monopolies may perform worse than competitive firms, what contradicts with the modern provisions of economic theory, stating that monopoly is the most lucrative type of market structure for a producer. The discovered effect occurs due to the aggressive pricing policy, adopted by monopolies, spurring up the inflation spiral, which is most obvious if monopolies are strongly interdependent in terms of production matrix. This inflation spiral drives prices too high, what negatively reflects on firms’ costs and, consequently, results in monopolies receiving less profit.

The proposed model can also be useful for understanding and assessing various economic consequences after different external or internal shocks, what is especially crucial when conducting monetary or fiscal policy.

This study aims to investigate the motivations behind the issuance of financial instruments with characteristics of equity (FICE), economic consequences associated with their issuance and accounting classifications based on a value-relevance approach.

Using a sample of 169 financial and nonfinancial firms from 10 jurisdictions that adopted International Financial Reporting Standards, the authors use a difference-in-differences econometric approach.

The findings reveal that FICE issuers are more leveraged companies with higher costs of equity and, in some cases, lower effective tax rates. This evidence corroborates the hypothesis that issuers of FICEs seek to increase their book values of equity (accounting treatment as equity) and, simultaneously, generate deductible expenses for tax purposes (tax treatment as liability).

This finding suggests that market participants do not treat these instruments as regular equity but rather as quasi-equity. The findings suggest that a binary classification of FICE as debt or equity may not be the accounting treatment that best represents the underlying economic substance of these contracts. Furthermore, this study reinforces the IASB indication regarding to increase the FICE disclosure to allow stakeholders to better understand the economic essence of these bonds.

This study assesses the economic outcomes and market evaluation of a specific type of FICE that has not been previously studied, which is similar to the examples provided by the IASB in their materials on the subject.

Customer lifetime value (CLV) is one of the key indicators to measure the success or health of an organization. How can an organization assess the organization's customers' lifetime value (LTV) and offer relevant strategies to retain prospective and profitable customers? This study offers an integrated view of different methods for calculating CLVs for both loyalty members and non-membership customers.

This study outlines eleven methods for calculating CLV considering (1) the deterministic aspect of NPV (Net present value) models in both finite and infinite timespans, (2) the geometric pattern and (3) the probabilistic aspect of parameter estimates through simulation modeling along with (4) the migration models for including “the probability that customers will return in the future” as a key input for CLV calculation.

The CLV models are validated in the context of complementary and alternative medicine (CAM)in the healthcare industry. The results show that understanding CLV can help the organization develop strategies to retain valuable customers while maintaining profit margins.

The integrated CLV models provide an overview of the mathematical estimation of LTVs depending on the nature of the customers and the business circumstances and can be applied to other business settings.

This paper aims to address the safety concerns of path-planning algorithms in dynamic obstacle warehouse environments. It proposes a method that uses improved artificial potential fields (IAPF) as expert knowledge for an improved deep deterministic policy gradient (IDDPG) and designs a hierarchical strategy for robots through obstacle detection methods.

The IAPF algorithm is used as the expert experience of reinforcement learning (RL) to reduce the useless exploration in the early stage of RL training. A strategy-switching mechanism is introduced during training to adapt to various scenarios and overcome challenges related to sparse rewards. Sensor inputs, including light detection and ranging data, are integrated to detect obstacles around waypoints, guiding the robot toward the target point.

Simulation experiments demonstrate that the integrated use of IDDPG and the IAPF method significantly enhances the safety and training efficiency of path planning for mobile robots.

This method enhances safety by applying safety domain judgment rules to improve APF’s security and designing an obstacle detection method for better danger anticipation. It also boosts training efficiency through using IAPF as expert experience for DDPG and the classification storage and sampling design for the RL experience pool. Additionally, adjustments to the actor network’s update frequency expedite convergence.

This paper examines the post-COVID-19 travel intentions to Kenya among Hong Kong outbound travelers using the theory of planned behavior (TPB) over three different time horizons of 1, 5, and 10 years.

An extension was made by including two new constructs of perceived destination image and travel constraints. A cross-sectional sample of Hongkongers was surveyed. Data were collected using a self-administrated bilingual (English and Chinese) online survey. Exploratory factor analysis, linear regression and mediation analysis were conducted to test the research model.

The findings from 216 Hongkongers reveal that different combinations of the four constructs, namely, perceived behavioral control, attitude, subjective norms, and destination image, share a positive effect on individuals' travel intention to Kenya over the three different time horizons. Travel constraints act as a significant negative mediator on the four constructs in predicting travel intention to Kenya among Hongkongers.

The results provide useful insight to Kenya's destination marketing organization (DMO) and Hong Kong outbound travel agencies to integrate prominent elements into marketing strategies to arouse travel intention and expand their business prospects, which will also accelerate tourism recovery in the post-pandemic era.

By integrating two extended variables into the TPB model, this study makes a contribution by overcoming the deficiency of the original theory.

Economic evaluations often utilise individual-patient data (IPD) to calculate probabilities of events based on observed proportions. However, this approach is limited when interest is in the likelihood of extreme biomarker values that vary by observable characteristics such as blood glucose in gestational diabetes mellitus (GDM). Here, instead of directly calculating probabilities using the IPD, we utilised flexible parametric models that estimate the full conditional distribution, capturing the non-normal characteristics of biomarkers and enabling the derivation of tail probabilities for specific populations. In the case study, we used data from the Born in Bradford study (N = 10,353) to model two non-normally distributed GDM biomarkers (2-hours post-load and fasting glucose). First, we applied fully parametric maximum likelihood to estimate alternative flexible models and information criteria for model selection. We then integrated the chosen distributions in a probabilistic decision model that estimates the cost-effective diagnostic thresholds and the expected costs and quality-adjusted life years (QALYs) of the alternative strategies (‘Testing and Treating’, ‘Treat all’, ‘Do Nothing’). The model adopts the ‘payer’ perspective and expresses results in net monetary benefits (NMB). The log-logistic and Singh-Maddala distributions offered the optimal fit for the 2-hours post-load and fasting glucose biomarkers, respectively. At £13,000 per QALY, maximum NMB with ‘Test and Treat’ (−£330) was achieved for a diagnostic threshold of fasting glucose >6.6 mmol/L, 2-hours post-load glucose >9 mmol/L, identifying 2.9% of women as GDM positive. The case study demonstrated that fully parametric approaches can be implemented in healthcare modelling when interest lies in extreme biomarker values.

Due to excessive carbon dioxide emissions, the world is facing environmental devastation. Energy and environmental innovations are considered to be critical tools in combating the growing CO₂ emissions. Developing these innovations requires extremely high investments in research and development processes, where knowledge is generated as one of the important outputs. This knowledge serves as a basis for innovation development and raising awareness among all relevant stakeholders about excessive environmental degradation. One of the significant sources of knowledge is scientific publications. Therefore, the aim of this research is to examine whether increased CO₂ emissions stimulate the scientific community to publish a greater number of papers, as well as whether the knowledge contained in these publications is utilized in reducing CO₂ emissions. The sample consists of G7 member countries. The time frame of the research is 1996–2019. The dynamic properties of the vector autoregression (VAR) models were summarized using impulse response function and variance decomposition forecast error. In most G7 countries, it has been determined that an increase in scientific production in environmental science and energy leads to a reduction in CO₂ emissions. On the other hand, increased CO₂ emissions affect higher scientific productivity in environmental science and energy only in Canada.

Drawing on the socioemotional selectivity theory and the volunteerism literature, this study aims to examine the influence of empathy, altruism and opportunity recognition, on social entrepreneurial intentions (SEI) of people who have retired from a full-time career. Furthermore, the study examines whether the above-mentioned relationships are mediated by moral obligation.

A set of hypotheses is tested by applying partial least squares structural equation modelling on a survey sample of 227 retirees in Oman, who had participated in an entrepreneurial leadership training after retirement. Using SmartPLS software, the path model is tested through bootstrapping.

The findings suggest that altruism and opportunity recognition do not have a direct relationship with SEI, however, they are significant only when mediated through moral obligation. Nevertheless, empathy has a significant direct association with SEI, and an indirect relationship through moral obligation.

The findings of this study demonstrate that to develop intentions to indulge in social entrepreneurship, among retirees who are approaching their senior years, the focus should be on driving their sense of moral obligation to society. Hence, policymakers and authorities connected to social wellbeing goals can fine-tune their initiatives, such as training, by emphasizing on moral obligation to address social issues through social entrepreneurship.

The novelty of this study is twofold. Firstly, to the best of the authors’ knowledge, it seems to be among the first empirical study that is at the crossroads of the senior entrepreneurship and the social entrepreneurship literature. Secondly, this study fills a gap in the extant literature by deploying the socioemotional selectivity theory to examine the antecedents of SEI of people who have retired from full-time employment in their early to late senior years.

This paper examines the extent to which exchange rate volatility (ERV) is crucial for small island economies. These economies by their very nature and size tend to be net importers and highly dependent on trade for their economic survival. The island of Mauritius is used as a case study.

A GARCH model has been utilized using yearly data for the period 1993–2022. The ARDL bounds cointegration approach has been used to determine the long run relationship between exchange rate volatility and the performance of exports. The ECM-ARDL model has been used to estimate the short-run relationships, that is the speed of adjustments between the variables under consideration.

The findings reveal that exchange rate volatility has a positive and significant effect on exports in the short run as well as in the long run. The study also finds out that export has a long-term relationship with world GDP per capita. Both the presence and degree of exchange rate volatility are important aspects for consideration in policy making.

The literature gap that this study attempts to close is one related to global impacts within the recent time horizon. Recently, numerous important events shaped the financial and economic landscape globally, including but not limited to the financial crisis of 2008 and the COVID-19 pandemic in 2019. Both these events stressed the global volume of trade and the exchange rate markets, and these events affects small islands comparatively more given their heavy dependence on international trade for economic development, albeit economic survival.

This study aims to provide a comprehensive review of electric tugboat deployment in maritime transportation, including an in-depth assessment of its advantages and disadvantages. Along with the identification of advantages and disadvantages of electric tugboat deployment, the present research also aims to provide managerial insights into the economic viability of different tugboat alternatives that can guide future investments in the following years.

A detailed literature review was conducted, aiming to gain broad insights into tugboat operations and focusing on different aspects, including tugboat accidents and safety issues, scheduling and berthing of tugboats, life cycle assessment of diesel tugboats and their alternatives, operations of electric and hybrid tugboats, environmental impacts and others. Moreover, a set of interviews was conducted with the leading experts in the electric tugboat industry, including DAMEN Shipyards and the Port of Auckland. Econometric analyses were performed as well to evaluate the financial viability and economic performance of electric tugboats and their alternatives (i.e. conventional tugboats and hybrid tugboats).

The advantages of electric tugboats encompass decreased emissions, reduced operating expenses, improved energy efficiency, lower noise levels and potential for digital transformation through automation and data analytics. However, high initial costs, infrastructure limitations, training requirements and restricted range need to be addressed. The electric tugboat alternative seems to be the best option for scenarios with low interest rate values as increasing interest values negatively impact the salvage value of electric tugboats. It is expected that for long-term planning, the electric and hybrid tugboat alternatives will become preferential since they have lower annual costs than conventional diesel tugboats.

The outcomes of this research provide managerial insights into the practical deployment of electric tugboats and point to future research needs, including battery improvements, cost reduction, infrastructure development, legislative and regulatory changes and alternative energy sources. The advancement of battery technology has the potential to significantly impact the cost dynamics associated with electric tugboats. It is essential to do further research to monitor the advancements in battery technology and analyze their corresponding financial ramifications. It is essential to closely monitor the industry’s shift toward electric tugboats as their prices become more affordable.

The maritime industry is rapidly transforming and facing pressing challenges related to sustainability and digitization. Electric tugboats represent a promising and innovative solution that could address some of these challenges through zero-emission operations, enhanced energy efficiency and integration of digital technologies. Considering the potential of electric tugboats, the present study provides a comprehensive review of the advantages and disadvantages of electric tugboats in maritime transportation, extensive evaluation of the relevant literature, interviews with industry experts and supporting econometric analyses. The outcomes of this research will benefit governmental agencies, policymakers and other relevant maritime transportation stakeholders.