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While servitization has been recognised for its potential to augment organizational revenue and fortify competitive advantage, the exploration of alternative servitization trajectories to the classical servitization model has been little explored in literature. Recent literature introduces the “service paradox” and presents different trajectories to the classical model, but it does not explain why a company chooses one trajectory instead of another. Therefore, this study aims to provide a model that, based on the contextual factors present, recommends which servitization trajectory the company should choose.

This study uses a combination of design science research (DSR) and context, intervention, mechanisms and outcomes (CIMO) to propose the model. An initial contextual factors list was created based on the literature, refined by the company’s employees and evaluated in three selected initiatives in the focal company. Furthermore, based on the understanding of the CIMO logic elements, four design propositions were elaborated to summarize the main findings of the study.

The study has demonstrated that the choice of a servitisation trajectory is intricately tied to a multitude of contextual factors, prompting organisations to deviate from conventional models towards alternative paths. Furthermore, the research sheds light on the underlying mechanisms and contextual drivers that shape servitisation decisions within the context of a consumer goods manufacturer. The analysis underscores the pivotal role of market dynamics and strategic adaptability in shaping servitisation strategies, underscoring the importance of customized approaches that cater to the distinct circumstances of each organisations.

The research contributes to both theory and practice by offering profound insights into the complex nature of servitisation, advocating for continuous adaptation and strategic alignment with market demands. For practitioners and decision-makers, the study provides valuable guidance on enhancing service offerings and navigating the complexities of servitisation within specific sectors, fostering a culture of learning and adaptation to drive sustainable growth.

This paper aims to examine the association between perceived firm risk and two reporting mechanisms: risk disclosure and earnings smoothing in the UK context.

This study juxtaposes three competing views, the “null”, the “divergence” and the “convergence” hypotheses, and empirically investigates whether risk disclosure and earnings smoothing affect firm perceived risk for a sample of large UK firms with rich and poor information environments. This study also uses the global financial crisis as an external shock on overall risk in the economy to investigate when and how managers use these two reporting mechanisms to shape the firm perceived risk.

This paper documents that risk disclosures have no significant effect on investors’ risk perceptions, consistent with risk disclosures containing boilerplate and generic statements about firm risk. This paper also finds that earnings smoothing reduces investors’ risk perceptions, reflecting investors’ interpretations about future firm performance. Additional tests reveal that earnings smoothing is not associated with perceived firm risk for firms with rich information environments and expanded risk disclosures. Furthermore, reporting smooth earnings decreases perceived firm risk following the global financial crisis. These findings are robust to alternative specifications and measures of earnings smoothing as well as post-filing perceived firm risk.

This study does not distinguish between the garbling role and the informational role of earnings smoothing. The risk disclosure measurement used in this study, developed based on UK annual reports, may limit the generalizability of findings to other countries.

The findings suggest that managers should revise their risk disclosure strategies to provide in-depth details on firm risk. Investors might require information and thorough assessment to evaluate investment risks when firms provide generic risk disclosures and smoothed earnings by consulting sources like financial intermediaries. Regulators should keep an eye on firms reporting boilerplate risk disclosures and on how smoothing earnings impacts the firm perceived risk following economic turmoil, to guide interventions that promote market stability.

The findings provide new insights into when and how managers use their financial reporting discretion to make firms appear less risky and, therefore, influence investors’ risk perceptions.

Several farm safety net strategies are available to farmers as a source of financial protection against losses due to price instability, government policies, weather fluctuations and global market changes. Producers can employ these strategies combining crop insurance policies with countercyclical policies for several crops and production areas; however, less is known about the efficiency of these strategies in enhancing profit and reducing its variability. In this study, we examine the efficiency of these strategies at minimizing inter crop year farm profit variability.

We utilized relative mean of profit and coefficient of variation, to compare counterfactually calculated farm safety net strategies for a sample of 28,615 observations across 2,486 farms and four dryland crops (corn, soybean, sorghum and wheat) in Kansas spanning nine crop years (2014–2022). A no farm safety net strategy is used as the benchmark for every alternative strategy to ascertain whether a policy customization is statistically different from a no farm safety case.

The general pattern of the results suggests that program combination strategies that have a high-profit enhancement potential necessarily have low profit risk for dryland wheat and sorghum production. On the contrary, such a connection is absent for dryland corn and soybeans production. Low-cost farm safety net strategies that enhance corn and soybeans profits do not necessarily lower profit risks.

This paper is one of the first to use a large sample of actual farm-level observations to evaluate how combinations of safety net programs offered under the Title I (PLC, ARCCO and ARCIC) and XI (FCIP) of the U.S. Farm Bill rank in terms of profit level enhancement and profit risk reduction.

This study aims to describe and empirically explore a new method for bank anti-money laundering (AML) systems using machine learning models. Current automated money laundering detection systems are notorious for flagging many false positives, causing bank employees to spend unnecessary time manually checking transactions that do not constitute money laundering. Decreasing the number of false positives can free up resources for investigating money laundering.

This study uses unique bank data on small- and medium-sized enterprises (SMEs) to examine how various client risk classification models can predict future suspicious transactions. This study explores various sources of client risk data and machine-learning approaches.

Client risk classification models can accurately predict suspicious future transactions. Adding accounting data and credit score information to client risk classification dramatically improves accuracy. This makes it easier to balance the risk of missing suspicious transactions with the need to reduce the number of false positives.

The suggested approach with readily available data sources and a focus on classifying client risk in a dynamic model can help banks significantly improve their efficiency by targeting their AML efforts toward the riskiest clients.

To the best of the authors’ knowledge, this study is the first to empirically explore machine learning in client risk classification, document how machine learning in client risk classification can significantly reduce false positives by incorporating novel, but readily available sources, such as credit risk and accounting data.

This study assesses the probability of an OECD member country exhibiting high persistence in unemployment duration, considering income inequality, productivity, accumulation of human capital and labor income share in Gross Domestic Product (GDP) between the years 2013–2019.

To achieve the purpose of the study, a probabilistic analysis with panel data is employed, focusing on 20 OECD countries segmented into two groups: those with high persistence and low persistence in unemployment duration. Probit and Logit models are estimated, marginal changes are analyzed and the models are evaluated in terms of their classification accuracy. Finally, trends in probabilities over time are examined.

This paper exhibits that countries with higher human capital index, greater labor income share in GDP, and more relevant productivity for well-being reduce their probabilities of experiencing high persistence in unemployment duration. It is observed that Mexico (MEX), Greece (GRC), Italy (ITA), and Turkey (TUR) have elevated probabilities of experiencing high persistence in unemployment duration in the future, while Costa Rica (CRI), Estonia (EST), Slovakia (SVK), Czech Republic (CZE), Lithuania (LTU), Poland (POL), and Israel (ISR) show a marked downward trend in these probabilities. Lastly, countries like the United Kingdom (GBR), Denmark (DNK), Sweden (SWE), Norway (NOR), Netherlands (NLD), Germany (DEU), United States (USA), and Canada (CAN) present minimal risk of experiencing high persistence in unemployment duration in the future.

The measurement of the relationship between development outcomes and persistence in unemployment duration has been scarce. Generally, the literature has focused on the analysis of development and unemployment without delving into the duration of unemployment, let alone persistence in duration.

This paper provides a solid foundation for the formulation of policies aimed at promoting sustainable employment and inclusive economic growth.

Based on the findings of the study, two key development policies are proposed. Firstly, the implementation of investment programs in Human Capital to increase productivity is recommended. Resources should be directed towards initiatives that improve the necessary skills and competencies in the labor markets of OECD countries, especially in strategic economic sectors with higher production linkages. Additionally, incentivizing the application of active labor policies is proposed. This entails prioritizing policies aimed at increasing the labor income share in GDP through progressive fiscal reforms that strengthen social safety nets and ensure fair labor standards. Implementing employment programs targeted at vulnerable groups, such as long-term unemployed individuals, youth, female heads of households and marginalized communities, is also recommended to eliminate structural barriers to labor market participation and reduce disparities in unemployment persistence. Adopting these policies can help mitigate the risk of high unemployment duration persistence and foster sustainable and inclusive long-term economic growth.

This is the first study to analyze the probabilities of both developing and developed countries experiencing high persistence in unemployment duration. It specifically evaluates these probabilities over a period of time and also estimates potential outcomes if real investments were made to enhance their human capital, productivity and employability.

The aim of this study is to identify environmental, social and governance (ESG)-focused funds that can effectively uphold ethical principles while also delivering competitive financial returns by evaluating the performance of 24 well-established exchange-traded funds (ETFs). The study also compares the performance of four widely recognized ETFs representing NASDAQ (ticker: QQQ), S&P500 (SPY), Dow Jones (DIA) and Russell 2000 (IWM) with the sample of 24 ESG funds.

This paper utilizes four complementary measures, namely Sharpe, Sortino, Omega and Calmar ratios, to assess the risk-adjusted return performance of ETFs, with a particular emphasis on extreme downside risk.

The findings indicate that ESG-focused ETFs can predominantly outperform DIA and IWM in the last five years (1 November 2018–22 March 2023). However, when compared to QQQ and SPY, only ICLN, SUSA and DSI consistently delivered competitive risk-adjusted returns. The performance of DSI and SUSA is almost equivalent to QQQ and SPY even during the last ten years.

The paper conducts a risk-return analysis of alternative ESG investment funds, suggesting that not all ETFs are created equal and that careful selection is vital for achieving different investment objectives. It is imperative to recognize that past performance is not a reliable indicator of future outcomes, requiring consideration of other factors in the post-evaluation phase.

The study provides evidence to support the “doing well while doing good” hypothesis, indicating that competitive returns are achievable while also engaging in socially responsible investment.

This study fills a vital gap in the literature on ESG investment by highlighting that the choice of funds stands as the primary factor responsible for the conflicting findings by previous studies.

This paper examines the impact of Central Bank Digital Currencies (CBDCs), regulated stablecoins and tokenized traditional assets on the cryptocurrency market, following the guidelines set by the Basel Committee. This study aims to analyze the implications for secure storage, cross-border transfers and necessary investments.

The paper uses a policy analysis approach to assess the potential effects of the Basel Committee’s regulations on CBDCs, regulated stablecoins and tokenized traditional assets. It explores their impact on the cryptoasset market, strategies of central and commercial banks, payment systems and risk management.

The adoption of CBDCs, regulated stablecoins and tokenized traditional assets is expected to grow rapidly in the coming years. It raises concerns about secure storage, cross-border transfers and required investments. Central banks are likely to introduce CBDCs and authorize stablecoin issuance, aiming for efficient monetary policies and risk management. Basel III regulations may lead to asset tokenization by banks, reducing asset size and increasing fee-based income.

This paper provides insights into the potential impact of the Basel Committee's regulations on CBDCs, regulated stablecoins and tokenized traditional assets. It contributes to the understanding of the evolving cryptoasset market and the strategies of central and commercial banks in adopting these technologies. The findings offer valuable information for policymakers, regulators and market participants in navigating the changing landscape of digital assets.

The demand for electric vehicles (EVs) has significantly increased in recent years, though some countries like Sri Lanka have reported the opposite direction compared to the global trend. Hence, this study focused on identifying factors affecting EV purchase intention and barriers to the widespread adoption of EVs in a developing country context. Also, this study presents an overview of the theoretical perspectives utilized for understanding consumer intentions and adoption behavior toward alternative fuel vehicles (AFVs).

The questionnaire method was employed, and 394 individuals who lived in Colombo City, Sri Lanka, with valid driving licenses and a hybrid or conventional vehicle were the study sample. The partial least squares structural equation modeling (PLS-SEM) was used to test the research hypothesis.

The findings confirmed that the three relationships between the unified theory of acceptance and use of technology (UTAUT) variables and EV purchase intention are significant, and there is no significant moderator effect from the consumer’s perceived risk.

These results offer useful information for governments and EV companies to better understand consumer behavior toward purchasing EVs.

The vulnerability of the tourism industry to an array of risks, encompassing family-related, small- and medium-sized enterprise-specific, strategic, tourism-specific and external factors, highlights the landscape within which small and medium family enterprises (SMFEs) operate. Although SMFEs are an important stakeholder in the dynamic tourism sector, they are not one homogenous group of firms, but have different strategic orientations. This study aims to investigate the interplay between strategic orientation and risk perception to better understand SMFEs risk perception as it is impacting their decision-making processes, resilience and long-term survival. The authors investigate how different strategic orientations contribute to different perspectives on risk among owner-managers.

Based on a qualitative data corpus of 119 face-to-face interviews, the authors apply various coding rounds to better understand the relationship between strategic orientations and the perceptions of risks. Firstly, the authors analysed the owner–manager interviews and identified three groups of different strategic orientations: proactive and sustainability-oriented SMFE, destination-affirmative and resilience-oriented SMFE and passive SMFE. Secondly, the authors coded the interviews for different risks identified. The authors identified that the three groups show differences in the risk perceptions.

The data unveil that the three groups of SMFEs have several differences in how they perceive risks. Proactive and sustainability-oriented SMFEs prioritize business risks, demonstrating a penchant for innovation and sustainability. Destination-affirmative and resilience-oriented SMFEs perceive a broader range of risks, tying their investments to destination development, emphasizing family and health risks and navigating competitive pressures. Passive SMFEs, primarily concerned with external risks, exhibit limited awareness of internal and strategic risks, resist change and often defer decision-making to successors. The findings underscore how different strategic orientations influence risk perceptions and decision-making processes within SMFEs in the tourism industry.

The authors contribute to existing knowledge include offering a comprehensive status quo of perceived risks for different strategic orientations, a notably underexplored area. In addition, the differences with respect to risk perception shown in the paper suggest that simplified models ignoring risk perception may be insufficient for policy recommendations and for understanding the dynamics of the tourism sector. For future research, the authors propose to focus on exploring the possible directions in which strategic orientation and risk perception influence one another, which might be a limitation of this study due to its qualitative nature.

Varying strategic orientations and risk perceptions highlight the diversity within the stakeholder group of SMFE. Recognizing differences allows for more targeted interventions that address the unique concerns and opportunities of each group and can thus improve the firm’s resilience (Memili et al., 2023) and therefore leading to sustainability destinations development. The authors suggest practical support for destination management organizations and regional policymakers, aimed especially at enhancing the risk management of passive SMFEs. Proactive SMFE could be encouraged to perceive more family risks.

Viewing tourism destinations as a complex stakeholder network, unveiling distinct risk landscapes for various strategic orientations of one stakeholder has the potential to benefit the overall destination development. The proactive and sustainability-oriented SMFEs are highly pertinent as they might lead destinations to further development and create competitive advantage through innovative business models. Passive SMFEs might hinder the further development of the destination, e.g. through missing innovation efforts or succession.

Although different studies explore business risks (Forgacs and Dimanche, 2016), risks from climate change (Demiroglu et al., 2019), natural disasters (Zhang et al., 2023) or shocks such as COVID-19 (Teeroovengadum et al., 2021), this study shows that it does not imply that SMFE as active stakeholder perceive such risk. Rather, different strategic orientations are in relation to perceiving risks differently. The authors therefore open up an interesting new field for further studies, as risk perception influences the decision-making of tourism actors, and therefore resilience.

This research paper aims to explore the concerns and determinants of travelers’ behavior toward ChatGPT in the hospitality and tourism context. It also examines the weight of risk factors versus that of motivation and innovation characteristics influencing travelers’ approach behaviors toward ChatGPT.

A cumulative prospect theory was used to determine travelers’ responses to ChatGPT. This study, using a fuzzy-set qualitative approach, explored risk, motivation and innovation factors as determinants of approach behaviors for ChatGPT.

Findings revealed that risk, motivation and innovation factors were the key triggers of approach behaviors for ChatGPT. An intricate combination effect of the perceived risk, motivation and innovation characteristics was found, and the necessary predictors were determined.

The findings of this study will expand our current knowledge and offer practical insights for the development of ChatGPT in the hospitality and tourism sector.

This study makes a significant contribution to the existing literature by providing a nuanced understanding of the intricate interplay between the various factors that shape customer behavior in the context of technology adoption in hospitality and tourism studies.