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The present research aims at identifying the latent factors that are driving the rise of the shadow economy in Palestine, assesses its magnitude from 1998 to 2021 and investigates the influence that its size has on the financial sustainability of Palestine's public budget.

The researchers employed the multi-indicator multi-causes (MIMIC) model to estimate the size of the shadow economy and investigate its effect on the financial sustainability of the public budget. Economic factors such as direct taxes, indirect taxes, government welfare, government spending and unemployment were considered causal variables, while indicators of financial sustainability included budget deficit, public debt and gross domestic product (GDP). The shadow economy served as an intermediary variable.

Based on the findings, the researchers recommend regulating and formalizing legitimate activities within the shadow economy. Additionally, they suggest promoting investment projects to reduce unemployment rates, lowering taxes on essential goods and consumer items and providing support to local producers in Palestine. These measures aim at addressing the challenges posed by the shadow economy and fostering economic stability.

The study reveals that the average size of the shadow economy in Palestine between 1998 and 2021 was 43.80%, fluctuating within the range of 39.92%–46.30%. It further establishes that an increase in direct and indirect taxes as well as unemployment contributes to the expansion of the shadow economy. Conversely, government welfare and spending exert a diminishing effect. Moreover, the study finds that the rise of the shadow economy correlates with an increase in public debt, budget deficit and GDP, indicating a negative impact on the financial sustainability of the public budget.

Inscrutable machine learning (ML) models are part of increasingly many information systems. Understanding how these models behave, and what their output is based on, is a challenge for developers let alone non-technical end users.

The authors investigate how AI systems and their decisions ought to be explained for end users through a systematic literature review.

The authors’ synthesis of the literature suggests that AI system communication for end users has five high-level goals: (1) understandability, (2) trustworthiness, (3) transparency, (4) controllability and (5) fairness. The authors identified several design recommendations, such as offering personalized and on-demand explanations and focusing on the explainability of key functionalities instead of aiming to explain the whole system. There exists multiple trade-offs in AI system explanations, and there is no single best solution that fits all cases.

Based on the synthesis, the authors provide a design framework for explaining AI systems to end users. The study contributes to the work on AI governance by suggesting guidelines on how to make AI systems more understandable, fair, trustworthy, controllable and transparent.

This literature review brings together the literature on AI system communication and explainable AI (XAI) for end users. Building on previous academic literature on the topic, it provides synthesized insights, design recommendations and future research agenda.

The purpose of this paper is to accelerate research related to the employee-facets of service management by summarizing current developments in multiple research streams, providing propositions, and articulating new directions for theory and empirical inquiry.

Seven scholars provide short reviews of the core topics and findings from four employee-related research streams – collective turnover, service climate, emotional labor, and occupational stress; and generate propositions to guide future theoretical and empirical work. Four distinguished service scholars – David Bowen, Ray Fisk, Christian Grönroos, and Jochen Wirtz comment upon these research streams and provide future directions for accelerating employee-related research in service management.

All four research-streams yield insights that have the potential to advance service management research. Commentaries from the distinguished scholars further integrate this work with key concerns within service management including technology-enablement, transformative services, and service strategy.

This paper is unique in its scope of coverage of management topics related to service and its aim to promote interdisciplinary dialog between service management scholars and researchers conducting employee-related research relevant to services.

The purpose of this paper is to investigate a novel approach toward electromagnetic launch.

The field of linear electromagnetic acceleration aims at accelerating macroscopic masses (up to several kg) to speeds in excess of 2 km/s. This can be achieved using accelerators of the railgun type. The innovation of this work lies in the use of multiphase current instead of the classically used quasi-direct current (DC). The approach taken is to work out in a first step the potential performance of such a configuration, for example, by showing that a constant propulsive force can be realized. Next, the necessary changes for the system setup were carefully analyzed. Both the accelerator and the power supply have to be considerably modified with regard to the classical approach.

Thorough analysis of the electromagnetic behavior of the launcher including nonlinear effects lead to an innovative system design which is considered to be the main finding of the work presented here. Moreover, a prototype was build. The preliminary experimental results obtained are in very good agreement with corresponding simulations validating the underlying modeling approach.

For the purpose of this paper, power levels of only 450 kVA are considered. However, this research can be used to design more powerful devices in the future.

While DC powered railguns are modeled very well in a variety of papers, the use of multiphase alternating current is not very well discussed yet. It could be of value for launch scenarios, for which very high speeds are required such as the launch of micro satellites to space.

In the presence of informal sector in the country, designing an energy policy and the pursuit of higher economic growth become challenging for emerging economies. These economies are usually resource starved, and the presence of underground economy leads to faulty estimates of energy demand. The authors explore the energy–growth nexus in the presence of underground economy for Pakistan, an emerging economy host to large informal sector and facing recurring energy crises.

The authors evaluate the impact of underground economy on energy demand in the presence of explanatory variables, including official gross domestic product (GDP), foreign direct investment and financial development. The authors first assess the influence of official economy on the consumption of energy. The authors investigate how energy consumption is influenced solely by underground economy. Finally, the authors evaluate the impact of true GDP on the energy consumption. The authors employ combined cointegration method of Bayer and Hanck (2013) and then apply vector error correction model.

The results reveal that official GDP, underground economy and true GDP positively and significantly affect energy consumption in both short and long run. Similarly, financial development as well as foreign direct investment enhance energy consumption. The authors find unidirectional causality between energy consumption and official GDP variables (OGDP → EC), underground economy (UE → EC) and true GDP variables (TGDP → EC) in the long run. The authors observe bidirectional causality in the short run between energy consumption and official GDP (OGDP ↔ EC) and true GDP (TGDP ↔ EC).

To the best of the authors' knowledge, no study examines the causal relationship of energy consumption and underground economy. Overall, the findings assist policymakers to consider and implement different energy-related policies considering the significant role of underground economy for energy consumption in Pakistan.

This paper aims to pose an important starting point for the application of the search-and-matching models to real estate appraisals, thus reducing the “gap” between practitioners and academicians. Due to relevant trading frictions, the search-and-matching framework has become the benchmark theoretical model of the housing market. Starting from the large related literature, this paper develops a simplified approach to modelling the frictions that focuses on the direct relationship between house price and market tightness (a common feature only for the labour market matching models). The characterization of the equilibrium through two main variables simplifies the analysis and allows using the theoretical model for empirical purposes, namely, the real estate appraisals.

This work is both theoretical and empirical. Theoretically, a long-run equilibrium model with a positive share of vacant houses and home seekers is determined along with price and market tightness. Also, the conditions of existence and uniqueness of the steady-state equilibrium are determined. Unlike most of the search-and-matching models in the housing literature, the out-of-the steady-state dynamics are also analyzed to show the stability of the equilibrium. Empirically, to show the usefulness of the theoretical model, a numerical simulation is performed. By using two readily available housing market data – the expected time on the market and the average number of trades – it is possible to determine the key variables of the model: price, market tightness and matching opportunities for both buyers and sellers. Although the numerical simulation concerns the Italian housing market, the proposed model is generally valid, being empirically applicable to all real estate markets characterized by non-negligible trading frictions. Indeed, the proposed model can be used to compare housing markets with different features (concerning the search and matching process), as well as analyse the same housing market in different time periods (because the efficiency of the search and matching process can change).

Several important results are obtained. First, the price adjustment – i.e. the difference between the actual selling price and the price obtained in an ideal situation of frictionless housing market – is remarkable. This means that the sign and the size of the price adjustment depend on the extent of trading frictions in the housing market. Precisely, the higher the trading frictions on the demand side (more buyers and less sellers), the higher the actual selling price (the price adjustment is positive), whereas the higher the trading frictions on the supply side (less buyers and more sellers), the lower the actual selling price (the price adjustment is negative). Accordingly, the real estate appraisers should assess the trading frictions in the housing market before determining the price adjustment. Second, an increase in the number of trades affects the house price only if the time on the market varies. Also, the higher the variation in the time on the market, the larger the house price adjustment. Indeed, the expected time on the market reflects the opportunities to matching for both parties and thus the trading frictions. If the time on the market increases (decreases), the seller will receive less (more) opportunities to match; thus, the actual selling price will be driven downwards (upwards).

As far as the authors are aware, none of the existing works in the search and matching literature has considered how to take advantage of this theoretical approach to estimate the house price in the presence of trading frictions in the housing market. Indeed, the proposed theoretical model may be a useful tool for real estate appraisers, as it is able to derive the trading frictions from the time on the market and the number of trades, thus estimating properly the house price.

This research examines how shadow economy affects foreign direct investment (FDI).

The study utilizes a panel dataset including 124 nations between 1997 and 2015. Information on shadow economy, FDI and macro-economic characteristics is obtained from the United Nations Conference on Trade and Development (UNCTAD) and World Bank database. Various econometric methods are employed, such as the panel ordinary least squares (OLS) with fixed-effect estimator and the two-step system generalized method of moments estimation.

The findings of the study illustrate that shadow economy negatively influences total FDI inflows, and this adverse impact is mainly driven by greenfield investments – a component of FDI. Moreover, the authors provide evidence that the shadow economy has more devastating influences on FDI inflows in countries with higher corruption levels and fewer land resources.

Overall, this research suggests an important policy implication that the shadow economy should be controlled more strictly since it harms the FDI inflows, especially greenfield investment.

This research is among the first attempt of evaluating the effect of shadow economy on different FDI types. Furthermore, it examines how the shadow economy–FDI inflows nexus is changed when considering factors including corruption and land resource.

This study aims to develop a conceptual model of service climate in hospitality, which tests its relationship with psychological capital (PsyCap), quality of work life (QWL) and turnover intention.

Data were collected among hotel employees by using an intercept approach and Qualtrics online survey system. Structural equation modeling examined the hypothesized relationships among the constructs in the conceptual model.

Service climate showed a positive relationship with PsyCap and QWL, and PsyCap partially mediated this relationship. Employees’ level of PsyCap had a powerful impact on QWL. Specifically, employee QWL was a critical mediator (full mediation) between service climate and turnover intention. Finally, PsyCap and QWL showed combined mediating effects between service climate and turnover intention.

This study extends the service climate literature in hospitality by offering a new conceptual model representing employees’ perceptions of service climate that influence their willingness to leave the organization with the mediating effects of PsyCap and QWL based on the theory of work adjustment.

The theory of work adjustment provides a deeper understanding of how employees’ perception of service climate affects their turnover intention in hospitality, based on a sample of hotel employees.

This study demonstrates the importance of service climate in understanding the turnover intention of hotel employees.

In many contemporary service organizations, service teams or service units are the main engines used to deliver key services to customers, client or patients. However, it remains unclear how teamwork mechanisms (i.e. the ways team members work together) influence customer service outcomes, and whether these relationships vary across different service contexts. To advance knowledge on the nature of teamwork in service teams and to set an agenda for further work in this area, there is a need to integrate and synthesize findings across the diverse literature on service teamwork. This paper aims to discuss the aforementioned objectives.

Using a meta-analytic approach, the authors analyzed a substantial pool of relevant effect sizes (a total of 372 effect sizes from 82 studies, with 14,291 service teams/units) to examine the effects of affective, behavioral, cognitive, motivational as well as perceptual teamwork mechanisms on customer service outcomes. The authors also investigated two key service context variables (service climate and service type) as boundary conditions on these effects.

The authors found that cognitive teamwork mechanisms were more strongly positively associated with customer evaluative outcomes than other mechanisms, whereas motivational and perceptual teamwork mechanisms had stronger associations with financial outcomes. Further, four of the five teamwork mechanisms demonstrated stronger correlations under a high service climate. The strength of the correlations between the teamwork mechanisms and customer service outcomes also exhibited different patterns when considered for different service types.

As with all meta-analysis, the quality of the primary studies influences the quality of the insights obtained from summarized effects. As most studies are cross-sectional design, the relationships examined in this paper cannot be interpreted causally. The authors cannot rule out the possibility of reverse causality, for example, reciprocal effects of customer service outcomes on teamwork dynamics due to the reciprocal feedback loop between customers and service providers.

The results hold important practical implications for enhancing customer evaluation and financial performance. First, the overall findings point to the need for employers to emphasize on certain types of teamwork training in order to encourage employee collaboration within service teams. For instance, service organizations could plan team building activities for service teams to promote trust, strengthen interpersonal bonds and improve problem-solving.

The results of this study provide an integration of previous research on service teamwork and fill two important gaps in the knowledge: (1) which aspect of teamwork is more important in determining customer service outcomes? And (2) does the effect of teamwork on customer service outcomes differ across different service contexts?

The purpose of this study is to examine the effect of service authenticity, customer participation (CP) and customer-perceived service climate on customers' service evaluation within the context of smartphone repair services in South Korea. A conceptual model, including customer-perceived service climate, service authenticity, CP, service value and service satisfaction, was proposed and tested.

The authors test the research model using a structural equation modeling approach (Amos) based on a mobile survey of 430 South Korean consumers. The authors design the research based on causal relationships and collect the data using the convenience sampling method.

The authors found that the independent variables (customer-perceived service climate, service authenticity and CP) have a positive effect on service value as well as service satisfaction. Further, service value has a mediating effect on the relationships between the independent variables and service satisfaction.

This is the first study to examine the effects of smartphone repair service on customers' evaluation. As the number of smartphone users increases, the results obtained from this study will provide important managerial implications for service managers.