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The purpose of the present study is to examine the effect of waiting lines on customers’ decisions between using a self-service alternative and using a service employee. As self-service technologies are expensive and time-consuming to design and implement, service providers need to understand what drives customers to use them. Service operators have the most control over waiting lines and flexibility in expanding capacity, either by adding service employees or by adding self-service kiosks.

The study used online scenario-based surveys following a 4 (number of customers waiting for the self-service technology) × 4 (number of customers waiting for the service employee) design. A binary dependent variable was used to record participants’ choice of service delivery alternative.

Using logistic regression, the authors found that customers are increasingly motivated to use self-service technology as the waiting line for the service employee grows longer. This effect is influenced by perceived usefulness, anticipated quality of the self-service technology, need for interaction and technology anxiety.

This study should be replicated in a real-world setting where actual behavior, and not only intention, can be measured.

The study provides guidance on how service providers can design their service to take advantage of the motivating effect of waiting lines on usage of self-service technology.

The present study is the first to combine a scenario-based experiment with a binary dependent variable to isolate the impact of waiting lines on the choice between using a self-service technology and using a service employee. The use of the binary dependent variable overcomes the ambiguity of extrapolating from a continuous measure of intention to draw conclusions about behavior, a binary variable.

This research aims to investigate the impacts of misleading hotel website photos on consumers’ brand trust, emotional responses and negative word-of-mouth (WOM) intention. The magnitude of these impacts in different contexts was examined.

This study employed a 2 (hotel segment: economy vs upscale) × 2 (expected product experience: hedonic vs utilitarian) scenario-based experimental design. A total of 240 consumers participated in this study.

The study results show that, in the case of misleading hotel website photos, brand trust was lower for the upscale hotel. Consumers experienced greater anger and regret in the upscale hotel situation and were most angry if they stayed at an upscale hotel for a hedonic purpose. The eWOM intention was higher in the upscale hotel situation. In addition, it was found that hotel physical environment was more important for female and married consumers.

A hypothetical brand name was used in this study. Therefore, brand attitude changes and the influences of brand loyalty on consumers’ responses to misleading website photos were not examined.

Upscale hotels and hotels that target leisure consumers need to make an effort to use truthful website photos and ensure that the physical environment is well maintained.

No prior research investigated the impact of misleading hotel website photos. This research fills this gap in the hospitality literature.

This paper aims to examine how stealing thunder, apology and compensation influence customer loyalty in a service failure context, and how trust mediates these relationships.

The study adopted a scenario-based between-group experimental design involving 300 customers.

The results indicated that stealing thunder, apology and compensation have a joint effect on customer loyalty. Specifically, this study found a significant positive impact of stealing thunder on loyalty; a two-way interaction effect of compensation and stealing thunder on loyalty; and a three-way interaction effect on loyalty. Additionally, trust mediated the relationship between service recovery attributes (stealing thunder, apology and compensation) and customer loyalty.

This study introduces a new service recovery method called Stealing Thunder, which is commonly used in the fields of law and communication and is the first to assess stealing thunder as a proactive/preemptive strategy to handle service failures and its impact on customer loyalty. The study found that when stealing thunder was present, compensation had no influence on customer loyalty. Moreover, when stealing thunder was present, compensation had no impact on loyalty when apology was not present. However, compensation had a significant effect on loyalty when stealing thunder and apology were not present. This study finds the value of including proactive/preemptive strategies (stealing thunder) along with regular service recovery strategies (e.g. apology and compensation) in the service recovery process. Results show that service recoveries that include stealing thunder help service failure recovery significantly by increasing customer’s trust.

One of the most basic pieces of information useful to hospitality operations is gross sales, and the ability to forecast them is strategically important. These forecasts could provide powerful information to cut costs, increase efficient use of resources, and improve the ability to compete in a constantly changing environment. This study tests sophisticated, yet simple‐to‐use time series models to forecast sales. The results show that, with slight re‐arrangement of historical sales data, easy‐to‐use time series models can accurately forecast gross sales.

This paper presents research results and implications in the literature for the last 15 years, and suggests guidelines on how to make the best use of the information to develop strategies that “fit” a service operation. There are considerable benefits of customer satisfaction, loyalty and increased profits from developing strategies to prevent service failures and strategies to successfully implement service recovery.

The paper proposes introducing a new antecedent to service recovery – that is customers' choice over some components of the service delivery process. The authors also examined the interactive effects of tangible compensation and apology on perceived fairness in a context of restaurant services.

A 2 (choice) × 2 (compensation) × 2 (apology) between‐subjects design was used to test the hypotheses. Subjects were exposed to a written scenario describing a restaurant experience. A total of 280 undergraduate students served as the subject pool.

The study results indicate that choice, compensation and apology jointly influence customers' perceptions of informational fairness. The combined effects of apology and compensation were observed for interactional fairness, whereas only main effects were found for distributive justice. Finally, the findings suggest that the four facets of justice (distributive, procedural, interactive, and informational) are highly linked to post‐recovery satisfaction.

Several limitations regarding this research should be kept in mind. First, students served as the sample pool for this investigation. Although the choice of students somewhat limits the generalizability of the results, the behaviors and responses of students and other market segments are likely to be more similar than different in service recovery incidents. Second, the manipulations involved absence and presence of three service recovery attributes (choice/no choice; compensation/no compensation, and apology/no apology). Consequently, different levels of these attributes might produce differential responses.

The findings of this study highlight the benefits of a proactive management of the service recovery process.

This research sheds some light on the role of choice in customer perceptions of service recovery processes. It also introduces a fourth dimension of justice – informational justice – to the service recovery literature.

This study aims to explore US hotel guests’ privacy concerns with a twofold aim as follows: to investigate the privacy categories, themes and attributes most commonly discussed by guests in their reviews and to examine the influence of cultural proximity on privacy concerns.

This study combined automated text analytics with content analysis. The database consisted of 68,000 hotel reviews written by US guests lodged in different types of hotels in five European cities. Linguistic Inquiry Word Count, Leximancer and SPSS software were used for data analysis. Automated text analytics and a validated privacy dictionary were used to investigate the reviews by exploring the categories, themes and attributes of privacy concerns. Content analysis was used to analyze the narratives and select representative snippets.

The findings revealed various categories, themes and concepts related to privacy concerns. The two most commonly discussed categories were privacy restriction and outcome state. The main themes discussed in association with privacy were “room,” “hotel,” “breakfast” and several concepts within each of these themes were identified. Furthermore, US guests showed the lowest levels of privacy concerns when staying at American hotel chains as opposed to non-American chains or independent hotels, highlighting the role of cultural proximity in privacy concerns.

Hotel managers can benefit from the results by improving their understanding of hotel and service attributes mostly associated with privacy concerns. Specific suggestions are provided to hoteliers on how to increase guests’ privacy and on how to manage issues related to cultural distance with guests.

This study contributes to the hospitality literature by investigating a neglected issue: on-site hotel guests’ privacy concerns. Using an unobtrusive method of data collection and text analytics, this study offers valuable insights into the categories of privacy, the most recurrent themes in hotel guests’ reviews and the potential relationship between cultural proximity and privacy concerns.

The purpose of this paper is to present a model to support governmental local managers in public budget optimization, based on an integration of methods. It was constructed to fill the gap related to weights definition in problematic, commonly performed subjective assessments. This model supports the decision making in budget distribution identifying the importance of sectors in local governments, captured by historical data.

The model was developed following three steps: the first step included the exploitation of the characteristics of local sectors represented by city departments and the data collection procedure using time series (TS). In the second one, the weights regarding the importance of each city department were calculated by the UTASTAR method and based on historical data from the first step. Finally, an objective function was formulated using linear programming and constraints based on law specifications, and as a result, an optimized projection for public budget distribution was performed.

The results demonstrated that the model can be more efficient to weights definition, considering the behavior of preferences by historical data and supporting local public resources optimization, also to comply with the legislation, being able to predict or project future values available on the budget.

The theoretical and practical implications are related with a novelty in recognizing the weights for criteria by a historical behavior of preferences. It can be bringing important directions for budget distribution. The main limitation detected in this study was the difficulty to formulate an assessment involving an integrated opinion from local managers and the population.

First of all, with the correct allocation of resources, the government has a greater advantage to capture investments from the negotiation with development entities and banks. Second, an efficient local government management can promote compliance with legislation and more transparent public policies.

The correct distribution of resources affects the life quality for citizens, since the government acts as a provider of essential services for the population like education, safety, health, particularly for citizens who depend exclusively on the services offered by the local government. Moreover, it can also affect the environment as resources for garbage collection, disposal services and sanitation and, finally, affect the city development such as infrastructure, taxes, etc.

It might be considered an original contribution mainly by the development of a procedure to capture values for weights by TS and meeting the manager’s requirements, based on analytical, statistical and mathematical tools integrated.

The cause of construction problems is suggested as being the lack of industry cohesion. This can only be addressed successfully by design professionals and construction professionals working more closely together, i.e. considering buildability. Buildability is a problem of managing the transfer of appropriate knowledge about the construction process to the design process worker. It is not solely about the technicalities of the construction process. It is suggested that no buildability strategy which seeks to impose predetermined construction solutions will be readily accepted by design professionals. The development of a design buildability strategy which transfers construction process knowledge in such a manner as to be seen as an adviser on simplification, would not be seen by design professionals as a convergent approach to buildability. Such a strategy would represent just one of a range of strategies to achieving overall project buildability.

COMING OUT firmly against a Government scheme for splitting jobs in their sectors is the Council of Civil Service Unions. They say that “The net effect of job‐splitting would be to create a number of part‐time posts from existing full‐time ones which will be seen as an unacceptable dilution of full‐time posts.”