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Despite the increasing attention given to product-service integration (PSI), little is known about this innovation strategy from a key decision-maker’s perspective. To address this gap, our study draws from personality psychology and decision-making (DM) logics theory to better understand why and how companies’ decision-makers strategize for PSI.

Using an abductive, empirics-first approach, we identify the study’s theoretical building blocks, followed by an exploratory quantitative analysis to generate new theory. We propose a fit-as-mediation conceptual framework suggesting that (1) specific personality traits [i.e. honesty-humility (H), emotionality (E), extraversion (X), agreeableness (A), conscientiousness (C) and openness to experience (O) (HEXACO)] make decision-makers more likely to include PSI in their company’s strategy and (2) depending on their personality, they apply different DM logics (i.e. causation or effectuation) to do so. To empirically examine this, we use data from 289 SMEs’ decision-makers.

We report several meaningful relationships among our key theoretical constructs. For instance, we find that conscientious decision-makers are more likely to develop a PSI strategy via causation, whereas extravert decision-makers are more likely to do so via both causation and effectuation.

This service study is the first to apply the well-established HEXACO Personality Inventory to companies’ key decision-makers. Moreover, it contributes to the microfoundations of PSI strategy and DM logic theories.

The purpose of this study is to provide a nuanced understanding of the marketing placebo effect (MPE) of products with reduced sugar labeling and how it forms certain perceptual underpins (perceived healthiness (PH) and perceived tastiness (PT)), with the potential effect of product category and social class in consideration.

The proposed model is tested using a sample of 822 participants by employing partial least squares structural equation modeling (PLS-SEM). Hypothetical relationships among MPE, PH, PT, purchase intention (PI) and social class are examined for both hedonic and utilitarian products.

The results highlight the positive role of MPE in leveraging consumer PI through the parallel mediation of PH and PT. The positive effect of MPE on PH and PT was more pronounced for the utilitarian product. In addition, social class negatively moderated the relationship between PH and PI only in the case of the utilitarian product.

This paper contributed to the MPE literature in the food industry by challenging the conventional intuition of “Unhealthy = Tasty” and highlighting the potential of perceived food healthiness to positively influence perceived food tastiness under the effect of MPE. An upper social class would attenuate the positive effect of perceived food healthiness on PI.

The present study aims to propose a framework elucidating the attributes of mobile augmented reality (AR) shopping apps (i.e., spatial presence, perceived personalization and perceived intrusiveness) and how they translate to downstream consumer-related outcomes (i.e., immersion, psychological ownership and stickiness to the retailer).

By conducting a questionnaire-based survey, 308 responses were collected, and the data were submitted to partial least square structural equation modeling (PLS-SEM) and artificial neural network (ANN) analyses.

A few important findings were generated from the present study. First, attributes of mobile augmented reality shopping apps (i.e., spatial presence, perceived personalization and perceived intrusiveness) influence stickiness to the retailer through immersion and consumer empowerment in serial. Second, immersion positively influences psychological ownership. Third, the optimum stimulation level moderates the relationship between spatial presence and immersion. Lastly, a post-hoc exploratory finding yielded by the multigroup analysis uncovered the moderating effect of gender.

This study offers a novel contribution to the smart retail literature by investigating the role of mobile AR shopping apps in predicting consumers' stickiness to the retailer. A holistic framework elucidating the serial mediating effect of immersion and consumer empowerment, and the moderating roles of optimum stimulation level and gender were validated.

The paper’s purpose is to consider, using a transaction cost economics (TCE) framework, the mechanisms used by space agencies to encourage private investment in the commercial spaceflight sector.

The authors conducted a content analysis of 554 pages of news articles, relating to issues pertaining to partnerships between national government-based space agencies and private space travel providers, published over a 20-year period. Leximancer was used to initially screen the data and then the authors manually analysed the content to identify themes.

The data analysis revealed three themes, relating to: the uncertainty of space travel; National Aeronautics and Space Administration (NASA) stimulating innovation in the private sector; and risk, insurance and regulation. These themes informed by TCE reveal the “hierarchical” organisational forms used to achieve human spaceflight and then the “hybrids”, insurance and regulations used to stimulate private sector investment and innovation.

This paper contributes to the accounting literature by answering the calls of Alewine (2020) and Tucker and Alewine (2022a, b) for more research into accounting in the space context. Specifically, the paper contributes by identifying mechanisms used by NASA to stimulate private investment in the space travel sector, as well as issues that have affected the implementation of these mechanisms. The paper also contributes to the literature by, based on the analysis, identifying a series of reflections designed to stimulate further management accounting research in the space context.

The use of generative artificial intelligence (genAi) language models such as ChatGPT to write assignment text is well established. This paper aims to assess to what extent genAi can be used to obtain guidance on how to avoid detection when commissioning and submitting contract-written assignments and how workable the offered solutions are.

Although ChatGPT is programmed not to provide answers that are unethical or that may cause harm to people, ChatGPT’s can be prompted to answer with inverted moral valence, thereby supplying unethical answers. The authors tasked ChatGPT to generate 30 essays that discussed the benefits of submitting contract-written undergraduate assignments and outline the best ways of avoiding detection. The authors scored the likelihood that ChatGPT’s suggestions would be successful in avoiding detection by markers when submitting contract-written work.

While the majority of suggested strategies had a low chance of escaping detection, recommendations related to obscuring plagiarism and content blending as well as techniques related to distraction have a higher probability of remaining undetected. The authors conclude that ChatGPT can be used with success as a brainstorming tool to provide cheating advice, but that its success depends on the vigilance of the assignment markers and the cheating student’s ability to distinguish between genuinely viable options and those that appear to be workable but are not.

This paper is a novel application of making ChatGPT answer with inverted moral valence, simulating queries by students who may be intent on escaping detection when committing academic misconduct.

This study aims to investigate the impact of regular Kung Fu and Taekwondo practice on the health and quality of life among elderly individuals in the Maule region, Chile.

The authors designed a 12-week Kung Fu and Taekwondo workshop with activities suitable for their age. Through semistructured interviews (at the beginning and the end of the workshop), along with periodic monitoring of vital signs and cardiovascular components, the authors observed an improvement in participants’ physical (strength, speed of reaction and flexibility) and psychological conditions (self-esteem and resilience), quality of life (relationships with family and friends and ability to deal with stressful events in working life) and health (waist circumference, percentage of oxygen saturation in blood, blood pressure, among other values).

From these results, the authors affirm that this workshop improves health and physical condition and helps the participants develop the coping capacity to deal with stressful situations and complicated interpersonal relationships. In this sense, the authors conclude that Kung Fu and Taekwondo as regular sports activities can benefit senior citizens’ aging process.

This research is based on an original study project.

The increased utilization of artificial intelligence-enabled applications (AI-ETs) across the customer journey has transformed customer experience (CX), introducing entirely new forms of the concept. This paper aims to explore existing academic research on the AI-enabled customer experience (AICX), identifying gaps in literature and opportunities for future research in this domain.

A systematic literature review (SLR) was conducted in March 2022. Using 16 different keyword combinations, literature search was carried across five databases, where 98 articles were included and analysed. Descriptive analysis that made use of the Theory, Characteristics, Context, Methods (TCCM) framework was followed by content analysis.

This study provides an overview of available literature on the AICX, develops a typology for classifying the identified AI-ETs, identifies gaps in literature and puts forward opportunities for future research under five key emerging themes: definition and dynamics; implementation; outcomes and measurement; consumer perspectives; and contextual lenses.

This study establishes a fresh perspective on the interplay between AI and CX, introducing the AICX as a novel form of the experience construct. It also presents the AI-ETs as an integrated and holistic unit capturing the full range of AI technologies. Remarkably, it represents a pioneering review exclusively concentrating on the customer-facing dimension of AI applications.

随着人工智能应用程序 (AI-ET)在旅途中的使用不断增加, 消费者体验 (CX)得以转变, 引入了全新的概念形式。 本文旨在探索有关人工智能客户体验（AICX）的现有学术研究, 从中找出文献中的空白以及该领域未来研究的机会。

本系统性文献综述（SLR）于2022 年 3 月开工。基于16 个不同的关键词组合, 本综述统共收录并分析了来自 5 个数据库98 篇文献, 采用理论-特征-背景-方法 (TCCM) 框架先后进行描述性分析和内容分析。

该研究概述了 AICX 的现有文献, 开发了对已识别的 AI-ET 进行分类的类型学, 确定了现有文献中的空白, 并在 5 个关键新兴主题下提出了未来研究的机会：1. 定义和动态, 2 . 实施, 3. 结果和衡量, 4. 消费者视角, 5. 情境视角。

本研究建立了全新的视角看待 AI 和 CX 之间的相互作用, 引入了 AICX 这种新颖的体验构造形式, 还将 AI-ET 展示为一个集成了全方位人工智能技术的整体单元。 值得一提的是, 本文代表了一项专门关注人工智能应用面向客户维度的开创性综述。

La creciente utilización de aplicaciones habilitadas por inteligencia artificial (AI-ET) a lo largo del recorrido del cliente han transformado la experiencia del cliente (CX), introduciendo formas totalmente nuevas del concepto. Este artículo pretende explorar la investigación académica existente sobre la experiencia del cliente a través de la IA (AICX), identificando las lagunas en la literatura y las oportunidades para futuras investigaciones en este ámbito.

En marzo de 2022 se llevó a cabo una revisión bibliográfica sistemática (SLR). Utilizando 16 combinaciones diferentes de palabras clave, se realizó una búsqueda bibliográfica en 5 bases de datos en las que se incluyeron y analizaron 98 artículos. El análisis descriptivo que hizo uso del marco Teoría, Características, Contexto, Métodos (TCCM) fue seguido del análisis de contenido.

El estudio ofrece una visión general de la bibliografía disponible sobre la AICX, desarrolla una tipología para clasificar las AICX detectadas, identifica lagunas en la literatura y plantea oportunidades para futuras investigaciones bajo cinco temas emergentes claves: 1. Definición y dinámica, 2. Implementación, 3. Resultados y medición, 4. Perspectivas del consumidor, 5. Lentes contextuales.

El estudio establece una nueva perspectiva sobre la interacción entre la IA y la CX, introduciendo la AICX como una forma novedosa del constructo experiencia. También presenta las AICX como una unidad integrada y holística que capta toda la gama de tecnologías de la IA. Notablemente, representa una revisión pionera que se concentra exclusivamente en la dimensión orientada al cliente de las aplicaciones de la IA.

This paper explores the different open science policy effects on the knowledge generation process of researchers in basic sciences: biology, chemistry and physics.

This paper uses a qualitative methodology with a content analysis approach. It uses seventeen semi-directed interviews.

The main perceived effect of open science is access to research inputs, with open access, open research data and code reuse as primary sources. Another issue is the increase of collaboration with other colleagues in terms of the ability to collaborate faster and encouraging the exchange of ideas. However, this benefit does not translate to the division of labor in large transnational teams. Time spent on tasks like cleaning up data and code, scooping and other ethical issues are unfavorable aspects noted.

Policymakers could use this study to enhance current open science policies in the countries.

This study analyzes the perspectives of basic sciences researchers from two countries about open science policies. The main conclusion is the fact that open science policies should focus on the research process itself – rather than research outputs – in order to effectively tackle inequalities in science.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-03-2023-0135

This research proposes to organise and distil this massive amount of data, making it easier to understand. Using data mining, machine learning techniques and visual approaches, researchers and managers can extract valuable insights (on guests' preferences) and convert them into strategic thinking based on exploration and predictive analysis. Consequently, this research aims to assist hotel managers in making informed decisions, thus improving the overall guest experience and increasing competitiveness.

This research employs natural language processing techniques, data visualisation proposals and machine learning methodologies to analyse unstructured guest service experience content. In particular, this research (1) applies data mining to evaluate the role and significance of critical terms and semantic structures in hotel assessments; (2) identifies salient tokens to depict guests' narratives based on term frequency and the information quantity they convey; and (3) tackles the challenge of managing extensive document repositories through automated identification of latent topics in reviews by using machine learning methods for semantic grouping and pattern visualisation.

This study’s findings (1) aim to identify critical features and topics that guests highlight during their hotel stays, (2) visually explore the relationships between these features and differences among diverse types of travellers through online hotel reviews and (3) determine predictive power. Their implications are crucial for the hospitality domain, as they provide real-time insights into guests' perceptions and business performance and are essential for making informed decisions and staying competitive.

This research seeks to minimise the cognitive processing costs of the enormous amount of content published by the user through a better organisation of hotel service reviews and their visualisation. Likewise, this research aims to propose a methodology and method available to tourism organisations to obtain truly useable knowledge in the design of the hotel offer and its value propositions.

This study aims to investigate stakeholders' perception of the most prevalent unethical practices in the Ghanaian construction industry.

Data used for this study came from a cross-sectional survey (questionnaire), which was administered to 273 stakeholders in the construction industry using convenience sampling technique. The data were analyzed using statistical software package SPSSv17 to determine the most prevalent unethical practices. The ranking factor was calculated based on relative importance index (RII) value.

The results of this study reveal that corruption was perceived by major stakeholders as the most prevalent unethical behavior (RII = 0.82) followed by bribery (RII = 0.79). Political interference and kickback came third (RII = 0.77) and fourth (RII = 0.74), respectively. However, the least prevalent unethical behaviors were extortion (RII = 0.56), workplace violence (RII = 0.57), alcohol abuse (RII = 0.59) and harassment (RII = 0.59). The findings suggest that when the various groupings were taken into consideration separately, the differences in their perceptions were obvious.

Data for this study were collected from construction stakeholders in Ghana who were conveniently sampled. As a result, in reference to the sampling framework which focused on major stakeholders in only two regions of Ghana does not sufficiently ensure full generalization of the results.

The findings of the study provide significant information for construction organizations and practitioners regarding unethical practices, which are most prevalent in the Ghanaian construction industry. Construction organizations and practitioners seeking to mitigate the negative effect of unethical practices on their performance should focus on educating construction workers on how to avoid corrupt practices and report same to the authorities. Also, ethics training programs must be instituted for staff coupled with constant and random inspection and checking of ethical compliance, verbal promotion and praise for ethical conduct and in some cases increase in employees pay.

This paper is one of the first to have accessed the views of broader stakeholders, i.e. consultants, contractors, professionals, suppliers, regulators, clients and construction workers in the construction industry regarding the most prevalent unethical practices in the Ghanaian construction industry in one study. This study, therefore, enriches the current literature by providing additional dimension to the understanding of unethical practices in the Ghanaian construction industry.