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The purpose of this study is to address a timely research question by clarifying whether formal planning is a worthy approach for hotels. In so doing, the authors developed a theoretical model that extends prior research by exploring how the formal planning process influences organizational capabilities and decision-making style. The model also examines the impact of the three identified factors on planning effectiveness.

Data were collected from 175 hotels located in United Arab Emirates (UAE) and Qatar and hypotheses were tested using structural equation modeling (SEM).

The study concludes that the practice of formal planning in the tourism sector does matter and both organizational capabilities and decision-making style are important factors in predicting planning effectiveness.

Generalizations to organizations operating in other sectors, such as manufacturing or government sectors, should be drawn cautiously.

Taking into account oil price volatility and serious political crises in the region, this study provides several insights to hotel managers into how the formal planning process can influence planning effectiveness.

The findings enrich the debate on the role of formal planning in the tourism sector, which has been relatively devoid of similar studies.

The role of managerial assumptions in the formulation of organizational strategies has been well recognized by previous studies, yet in marketing literature, the effect of such imperative on marketing practice choice tends to be ignored. Therefore, this paper aims to empirically investigate how management assumptions fit with the choice of marketing practices, and how such fit affects performance.

A model is developed and tested using survey methodology, and the data are analyzed using the partial least square (PLS) approach.

The results show that different marketing practices were coupled with different frames of reference, resulting in viable matching profiles.

Given the novelty of the approach adopted in this study, conclusions about association and not causation are drawn. In addition, the study is restricted to Qatar which may reduce the generalizability of its findings and conclusions.

The findings will help managers to examine carefully the internal logic of their marketing-related profiling, where coherent variables will enhance performance.

To one’s knowledge, this paper reports a work in an area not previously researched. In addition, this study is one of the rare papers that examines unobserved heterogeneity using the PLS-structural equation modeling (SEM) in the field of marketing.

Information Systems research on emotions in relation to using technology largely holds essentialist assumptions about emotions, focuses on negative emotions and treats technology as a token or as a black box, which hinders an in-depth understanding of distinctions in the emotional experience of using artificial intelligence (AI) technology in context. This research focuses on understanding employees' emotional experiences of using an AI chatbot as a specific type of AI system that learns from how it is used and is conversational, displaying a social presence to users. The research questions how and why employees experience emotions when using an AI chatbot, and how these emotions impact its use.

An interpretive case study approach and an inductive analysis were adopted for this study. Data were collected through interviews, documents review and observation of use.

The study found that employee appraisals of chatbots were influenced by the form and functional design of the AI chatbot technology and its organisational and social context, resulting in a wider repertoire of appraisals and multiple emotions. In addition to positive and negative emotions, users experienced connection emotions. The findings show that the existence of multiple emotions can encourage continued use of an AI chatbot.

This research extends information systems literature on emotions by focusing on the lived experiences of employees in their actual use of an AI chatbot, while considering its characteristics and its organisational and social context. The findings inform the emerging literature on AI.

The purpose of this paper is to gain insight into the contingent use of rational, intuitive and political decision-making in R&D.

This research is based on a study in an R&D department of a multinational high-tech firm in the Netherlands. The study consists of a case study design, focusing on four embedded cases, longitudinally studying each case.

The literature distinguishes three dimensions of innovation decision-making processes: rational, intuitive and political. By studying these interwoven dimensions over time, this study finds that the dominant use of each of these dimensions differs across the innovation process. There is an emphasis on intuitive decision-making in an early phase, followed by more emphasis on political decision-making, and moving to more emphasis on rational decision-making in a later phase of the R&D process. Furthermore, the predominant choice in a specific innovation phase for one of the three decision-making dimensions is influenced by the decision-making dimension that is dominantly employed in the preceding phase.

This study contributes to the innovation decision-making literature by developing and applying a model that distinguishes rational, intuitive and political decision-making dimensions, the interactions among these dimensions in innovation decision-making in R&D, and the contingency of these dimensions upon the innovation phase. It calls for further research into the contingent nature of innovation decision-making processes.

For practitioners this study has two relevant insights. First it highlights the importance and usefulness of intuitive and political decision-making in addition to the prevailing emphasis on rational decision-making. Second, practitioners may be more alert to consciously changing their dominant decision-making approach across the phases of the innovation process. Third, companies may adjust their human resource policies to this study’s findings.

The literature on rational, intuitive and political decision-making is quite extensive. However, research has hardly studied how these decision-making dimensions develop in conjunction, and over time. This paper reports on a first study to do so and finds that the dominant use of these dimensions is contingent upon the phase of the R&D process and on the decision-making dimensions used in earlier phases. The study suggests that using a contingency approach can help to further integrate the debate in research and practice.

While the proliferation of chatbots allows companies to connect with their customers in a cost- and time-efficient manner, it is not deniable that they quite often fail expectations and may even pose negative impacts on user experience. The purpose of the study is to empirically explore the negative user experience with chatbots and understand how users respond to service failure caused by chatbots.

This study adopts a qualitative research method and conducts thematic analysis of 23 interview transcripts.

It identifies common areas where chatbots fail user expectations and cause service failure. These include their inability to comprehend and provide information, over-enquiry of personal or sensitive information, fake humanity, poor integration with human agents, and their inability to solve complicated user queries. Negative emotions such as anger, frustration, betrayal and passive defeat were experienced by participants when they interacted with chatbots. We also reveal four coping strategies users employ following a chatbots-induced failure: expressive support seeking, active coping, acceptance and withdrawal.

Our study extends our current understanding of human-chatbot interactions and provides significant managerial implications. It highlights the importance for organizations to re-consider the role of their chatbots in user interactions and balance the use of human and chatbots in the service context, particularly in customer service interactions that involve resolving complex issues or handling non-routinized tasks.