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The paper faces artificial intelligence issues in the venture creation process, exploring how artificial intelligence solutions intervene and forge the venture creation process. Drawing on the most recent literature on artificial intelligence and entrepreneurship, the authors propose a set of theoretical propositions.

The authors adopt a multiple case approach to assess propositions and analyse 4 case studies from which the authors provide (1) more detailed observation about entrepreneurial process phases influenced by artificial intelligence solutions and (2) more details about mechanics enabled by artificial intelligence.

The analysis demonstrates artificial intelligence contributes alongside the entrepreneurial process, enabling mechanisms that reduce costs or resources, generate new organizational processes but simultaneously expand the network needed for venture creation.

The paper adopts a deductive approach analyzing the contribution of AI-based startup offerings in changing the entrepreneurial process. Thus, the paper provides a practical view of the potentiality of artificial intelligence in enabling entrepreneurial processes through the analysis of compelling propositions and the technological ability of artificial intelligence solutions.

As quarterly business reviews (QBRs) remained unexplored in the scholarly community, this paper sheds light on what QBRs are, how they are being used across organisations and provides deep insights into the implementation of the QBR at an incumbent car manufacturer’s digital transformation business unit. Particular attention has been paid to decision processes, portfolio management, challenges and success factors.

Given the explorative nature of the research, a case study is well suited to explore the phenomenon in its real-world context, especially given the dynamic and volatile business environment. This article is based on insights from an incumbent car manufacturer undergoing a business-wide transformation.

The car manufacturer introduced the QBR process and themes to improve business effectiveness and efficiency through (1) focusing on the biggest issues, (2) concentrating efforts, (3) providing autonomy and stability, (4) building and maintaining strong relationships, and (5) building domain expertise. Through the QBR process, themes were (de)prioritised, resources allocated, financial value (estimates) agreed upon, and key performance indicators (e.g. £m/FTE; FTE, full-time equivalent employees) introduced. Digital product managers’ were assigned to the prioritised themes, and portfolio management structures were presented.

Managing short- and long-term objectives is challenging for most businesses but essential to perform well in uncertain environments. The QBR process can help organisations continuously (de)prioritise work and reallocate resources based on changing environments and aligned with strategic priorities.

This study is intended to motivate and guide future researchers to rethink and update their theories of operational capability development. By examining the extensive body of research on operational capabilities and working closely with an industry partner, the authors are iteratively developing new thinking about why our existing models seem to be failing and what aspects are likely to be useful in updating them.

This pathway paper is based on observations gained through a structured literature review, close collaboration with an industry partner and discussions with other industry partners and executives.

The authors identify ways in which the operations management community could begin to challenge and expand existing models of operational capability development. They provide reflections on the network structure of operational capabilities, i.e. their interconnectedness and interactions, which are likely to evolve dynamically over time and have not yet been part of the authors’ thinking about operational capability development.

The authors hope to stimulate new research through this pathway paper. By synthesizing their existing knowledge of operational capabilities and collaborating with an industry partner, the authors have attempted to highlight their limited knowledge of capability development. In addition, the authors offer several opportunities to rethink their existing models.

As stated in the United Nations Global Assessment Report 2022 Concept Note, decision-makers everywhere need data and statistics that are accurate, timely, sufficiently disaggregated, relevant, accessible and easy to use. The purpose of this paper is to demonstrate scalable and replicable methods to advance and integrate the use of earth observation (EO), specifically ongoing efforts within the Group on Earth Observations (GEO) Work Programme and the Committee on Earth Observation Satellites (CEOS) Work Plan, to support risk-informed decision-making, based on documented national and subnational needs and requirements.

Promotion of open data sharing and geospatial technology solutions at national and subnational scales encourages the accelerated implementation of successful EO applications. These solutions may also be linked to specific Sendai Framework for Disaster Risk Reduction (DRR) 2015–2030 Global Targets that provide trusted answers to risk-oriented decision frameworks, as well as critical synergies between the Sendai Framework and the 2030 Agenda for Sustainable Development. This paper provides examples of these efforts in the form of platforms and knowledge hubs that leverage latest developments in analysis ready data and support evidence-based DRR measures.

The climate crisis is forcing countries to face unprecedented frequency and severity of disasters. At the same time, there are growing demands to respond to policy at the national and international level. EOs offer insights and intelligence for evidence-based policy development and decision-making to support key aspects of the Sendai Framework. The GEO DRR Working Group and CEOS Working Group Disasters are ideally placed to help national government agencies, particularly national Sendai focal points to learn more about EOs and understand their role in supporting DRR.

The unique perspective of EOs provide unrealized value to decision-makers addressing DRR. This paper highlights tangible methods and practices that leverage free and open source EO insights that can benefit all DRR practitioners.

Digital transformation affected modern society influencing how businesses cooperate and produce value. In this context, Artificial Intelligence plays a critical role. This study aims to explore the role of Artificial Intelligence in organisational positioning within the market, influencing firms' competitiveness. In this vein, this research seeks to respond to the following research question: How does AI impact the competitive advantage of healthcare organizations?.

To tackle the research question, an explorative analysis using the case study method to investigate an international healthcare center in Dubai was conducted. Nine semi-structured interviews were conducted with the head and the members of the robotic surgery team in CMC Dubai to thoroughly understand what the components of the robotic approach are and how the arrangement before the introduction of this innovative technique while shedding light on the added value and the advantages of adopting such technique on both patient safety and patient satisfaction. Additionally, archival data and online documentation (e.g. industry reports, newspaper articles and internal documents) were analyzed to obtain data triangulation.

The results highlight three primary outcomes influenced by implementing AI in organizational processes: clinical, financial and technological outcomes. The study will offer interesting non-studied insights about the implementation of Artificial Intelligence tools in the healthcare sector and specifically robotic surgeries, and to which extent this will contribute and represent a competitive advantage. Results will hopefully insert a brick in the wall of the impact of AI tools on the quality and the results of surgical operations while emphasizing the benefits of integrating AI in surgical practice.

This study offers interesting theoretical and practical implications. It opens a new perspective to understand and manage AI tools in service. This research is not without limits providing valuable insights for future research.

Improving and assuring the quality of higher education has become a key element of policy agendas worldwide. To this end, a complete accountability system has been developed through various evaluation procedures. Specifically, this study analyzes the perceptions of university teaching staff on the impact of performance appraisal systems on their professional activity, health and personal lives.

The study adopted a nonexperimental descriptive and causal-comparative design using a questionnaire that was completed by a sample of 2,183 Spanish teachers. The data obtained were analyzed using descriptive statistics and comparisons of differences.

The results show that, according to teachers, the evaluation criteria undermine the quality of their work by encouraging them to neglect teaching, increase scientific production and engage in unethical research practices. Their views also emphasize the social and health-related consequences of an increasingly competitive work climate, including increased stress levels. Finally, significant differences are observed regarding gender, professional category and academic discipline, with women, junior faculty and social sciences teachers expressing particularly strong views.

The originality of this study lies in the application of a method that contributes to the international debate through a national perspective (Spain) that has so far received little attention.

Managing projects is an important part of operations management, but many projects fail. This study focuses on attribution processes of such disruption from the underrepresented perspective of the project manager. The authors consider two types of causes: the more frequently researched environmental uncertainty (i.e. uncontrollable events) and the scarcely researched uncertainty imposed by non-collaborative project sponsors (i.e. other-controllable events).

The authors test conceptual arguments grounded in attribution theory and the notion of psychological contracts in a scenario-based experiment among 325 practicing project managers.

The findings indicate that non-collaborative project sponsors negatively affect project managers' motivation, whereas uncontrollable disruptions leave hope to achieve positive future outcomes. This latter effect is further strengthened when project managers have an internal attribution style. They tend to blame the disruption on themselves and generally feel in control of achieving success even if they are not.

These socio-psychological insights nuance the economic idea that uncertainty reduces motivation per se in the context of project disruption appraisal. The authors contribute to the behavioral project management literature and general attribution theory and help guide the allocation of resources during the recovery of failed projects.

Adventure activities have become the core products of many tourism destinations. Hiking, which is known to be a soft adventure activity, represents an especially important product for many tourism destinations around the globe and in the European Alps. However, little research has explored hikers’ underlying motivation and experiences, which are expected to differ from the hard adventure context, as mountain hiking provides a low risk, but high immersion. This paper aims to determine and explore the underlying dimensions and dynamics of mountain hikers’ soft adventure motivation (SAM).

A concurrent mixed-method design that builds on a quantitative survey (N = 379) and qualitative interviews (N = 14) was used to explore SAM factors. This study combined exploratory factor analysis and regression analysis with semi-structured interviews and template analysis.

The quantitative results provide six SAM factors and emphasize that “relaxation,” “socializing” and “discovery” contribute to hiking satisfaction, while “recognition” has adverse effects. By triangulating these findings with hikers’ experiences, this study underlines the associated recreational meaning of hiking and provides an in-depth qualitative discussion of SAM factors and the subordinate role of “recognition.”

The contribution of this paper is a refined understanding of SAM in the hiking context by emphasizing the recreational meaning of mountain hiking. As a result, this study adds an important missing link to previous outdoor tourism and leisure studies by showing the special composition and dynamics of SAM. The findings also support the creation of tailor-made touristic products.

探险活动已经成为许多旅游目的地的核心产品。其中徒步旅行被认作为一种“轻松”探险活动并且代表着全球众多旅游目的地及欧洲阿尔卑斯山的重要产品。然而, 很少有研究探索远足者的潜在动机和经验, 由于徒步远足的风险较低, 但参与感高, 因此预计于艰苦的冒险环境有所不同。因此, 本文确定并探索了山地徒步者“轻松”冒险动机的潜在维度和动力。

采用基于定量调查(N = 379)和定性访谈(N = 14)的并行混合方法设计来探索SAM因素。因此, 我们将探索性因子分析和回归分析与半结构化访谈和模板分析相结合。

定量结果提供了6个SAM因素, 并强调“放松”、“社交”和“发现”有助于提升满意度, 而“认知”则有负面影响。通过将这些发现与徒步旅行者的经历进行三角分析, 我们强调了徒步旅行的相关娱乐意义, 并对SAM因素和“识别”的从属作用进行了深入的定性讨论。

本文的贡献在于通过强调登山的休闲意义, 对徒步情景下的SAM进行了精细化的理解。因此, 我们通过展示SAM的特殊组成和动态, 为之前的户外旅游和休闲研究添加了一个重要的缺失环节。最后, 研究结果支持了定制旅游产品的创造。

探险旅游, 动机, 软探险, 徒步

研究论文

Las actividades de aventura se han convertido en uno de los productos principales de muchos destinos turísticos, especialmente el senderismo, una actividad de aventura de baja dificultad que representa un producto importante para muchos destinos turísticos alrededor del mundo y en los Alpes europeos. Sin embargo, pocas investigaciones han estudiado la motivación y las experiencias subyacentes de los excursionistas, las cuales se espera que difieran del contexto de aventura de alta dificultad, ya que el senderismo de montaña proporciona un bajo riesgo pero una alta inmersión. Por lo tanto, este documento determina y examina las dimensiones y dinámicas subyacentes de la motivación de aventura de baja dificultad (SAM, por sus siglas en inglés) de los excursionistas de montaña.

Se utilizó un diseño de método mixto concurrente que se basa en una encuesta cuantitativa (N = 379) y entrevistas cualitativas (N = 14) para explorar los factores de SAM. De este modo, se combinó análisis factorial exploratorio y análisis de regresión con entrevistas semiestructuradas y análisis de plantillas.

Los resultados cuantitativos aportan seis factores de SAM y enfatizan que la “relajación”, la “socialización” y el “descubrimiento” contribuyen a la satisfacción del senderismo, mientras que el “reconocimiento” tiene efectos adversos. Al relacionar estos hallazgos con las experiencias de los excursionistas se destaca el significado recreativo asociado al senderismo y se brinda una discusión cualitativa profunda de los factores de SAM y el papel subordinado del “reconocimiento”.

La contribución de este artículo es una comprensión refinada de la SAM en el contexto de senderismo al enfatizar el significado recreativo del senderismo de montaña. De este modo, se suma un importante eslabón perdido a los estudios anteriores de turismo al aire libre y de ocio al mostrar la composición y dinámica especial de la SAM. Por último, los resultados respaldan la creación de productos turísticos hechos a la medida de las preferencias de los turistas.

This paper aims to explore how tensions and alignments between different actors’ needs in a transformative services network affect balanced centricity, which is an indicator of well-being. Balanced centricity describes a situation in which all network actors’ interests and needs are fulfilled simultaneously. In such cases, all actors are better off, which increases both individual actors’ and overall actor-network well-being.

The empirical study takes place in nursing homes in which in-bed baths represent co-created service encounters that affect the well-being of focal actors (i.e. patients), frontline service employees (i.e. nurses) and transformative service mediators (i.e. family members), who have potentially competing needs. Using a qualitative, phenomenological approach, the study inductively explores and deductively categorizes actors’ personal experiences to gain deep, holistic insights into the service network and its complex web of actor interdependencies.

The resulting conceptual model of balanced centricity identifies actors’ lower-order needs as different manifestations of the psychological needs for autonomy, competence and relatedness. If actors’ needs are aligned, their psychological needs can be satisfied, which facilitates balanced centricity. If actors exhibit competing needs though, balanced centricity is impeded.

This study establishes actors’ psychological needs as the origin of tensions/alignments in multi-actor networks that impede/contribute to balanced centricity. Transformative service providers should try to address all actors’ psychological needs when co-creating services to achieve network well-being.

This study adopts a novel, multi-actor perspective and thereby presents a conceptual model that contributes to the understanding of balanced centricity. Future research could test this model in other transformative service settings.

Artificial intelligence (AI) has started to receive attention in the field of digital entrepreneurship. However, few studies propose AI-based models aimed at assisting entrepreneurs in their day-to-day operations. In addition, extant models from the product design literature, while technically promising, fail to propose methods suitable for opportunity development with high level of uncertainty. This study develops and tests a predictive model that provides entrepreneurs with a digital infrastructure for automated testing. Such an approach aims at harnessing AI-based predictive technologies while keeping the ability to respond to the unexpected.

Based on effectuation theory, this study identifies an AI-based, predictive phase in the “build-measure-learn” loop of Lean startup. The predictive component, based on recommendation algorithm techniques, is integrated into a framework that considers both prediction (causal) and controlled (effectual) logics of action. The performance of the so-called active learning build-measure-predict-learn algorithm is evaluated on a data set collected from a case study.

The results show that the algorithm can predict the desirability level of newly implemented product design decisions (PDDs) in the context of a digital product. The main advantages, in addition to the prediction performance, are the ability to detect cases where predictions are likely to be less precise and an easy-to-assess indicator for product design desirability. The model is found to deal with uncertainty in a threefold way: epistemological expansion through accelerated data gathering, ontological reduction of uncertainty by revealing prior “unknown unknowns” and methodological scaffolding, as the framework accommodates both predictive (causal) and controlled (effectual) practices.

Research about using AI in entrepreneurship is still in a nascent stage. This paper can serve as a starting point for new research on predictive techniques and AI-based infrastructures aiming to support digital entrepreneurs in their day-to-day operations. This work can also encourage theoretical developments, building on effectuation and causation, to better understand Lean startup practices, especially when supported by digital infrastructures accelerating the entrepreneurial process.