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The paper aims to explore the value generated by a specific configuration of a smart city's infrastructure by proposing a comparison between a silos configuration versus a crowd configuration at the data storage and processing level.

A system dynamics simulation is adopted to determine and compare the value created by the two configurations of smart city's infrastructure. The simulation outlines the flow of data and their positive and negative feedback that reinforce and hinder the smart city value generation.

The results demonstrate the huge impact of the availability of data for App developers when crowdsourcing configuration is adopted. Furthermore, results unveil the potential in value generation of a crowdsourcing smart city platform configuration compared to a silos architecture.

The authors have proposed a comparison between two alternative smart city digital platform configurations. The paper seeks to test the magnitude of the pros and cons of a crowdsourcing approach in setting up a smart city digital platform. The paper provides new guidelines for improving the data management of smart cities.

The purpose of this paper is to examine the role of founding team experience (industry and venturing) in new venture creation. This paper posits the following questions: How does founding team experience influence the likelihood of new venture creation, in the nascent stage? How does industry context moderate this relationship? The study aims to fill an important gap in the literature by unpacking the impact of different types of founding team experiences on venture outcome, and by focusing on the influence of founding team in the venture creation process, specifically at the nascent stage.

The paper utilizes data from the Second Panel Study of Entrepreneurial Dynamics, a longitudinal data set of 1,214 nascent entrepreneurs in the USA. Logistics regression was employed to analyze the effect of founding team experience on new venture creation. Post hoc analysis was conducted to ensure the confidence of the findings.

The paper provides empirical insights about how founding team experience influences the likelihood of new venture creation in the nascent stage. At the nascent stage, founding team industry experience positively affects new venture creation while founding team venturing experience does not. However, in the high-technology industry environment, the influence of the founding team’s venturing experience on new venture creation is stronger than that in the low-technology industry environment.

Due to the design of the data set, there is a risk of “right-censoring” problem. Also, because the study used archival data on founding teams, the methodology did not allow for uncovering the underlying team processes and dynamics during the venture creation process based on learning from experience. Future studies are encouraged to examine other types of founding team experience and the underlying process-level factors on venture creation.

The paper provides important practical implications for nascent entrepreneurs/entrepreneurial teams on team assembling and composition. In general, a team with higher-level industry experience is critical for venturing success. A team with higher-level venturing experience is more desired in the high-technology industry.

This paper fulfills an important gap in the entrepreneurial team literature by highlighting the complex and nuanced ways in which founding team experience influences the likelihood of venture creation in the nascent stage of the firm, especially after incorporating the additional impact of the industry context.

This paper examines in detail how the use of storytelling with parallax technology can influence the user experience (UX) in online shops as well as brand- and behavior-relevant variables. Furthermore, this study analyzes the causal relationships between UX, brand attitudes and brand-related behavioral intentions in terms of purchase intention and price premiums. Explicit and implicit paths of human information processing are considered.

A sample of 266 respondents completed a web-based experiment under two conditions (text-based vs parallax storytelling online shop). An existing and operational online shop was used. The causal relationships were assessed by using partial least squares structural equation modeling (PLS-SEM). To measure implicit information processing, a single category implicit association test was applied.

By applying the storytelling technique with parallax scrolling, the online shop increased visitors' UX on explicit and implicit information processing levels and increased the online shop's overall perceived attractiveness. Storytelling with parallax motion enables an efficient transmission of brand-related associations to consumers' minds, enhances their explicit and implicit brand attitudes and increases their willingness to pay a higher price. Moreover, this study provides empirical evidence on the effects of UX on brand-related measures by applying PLS-SEM and thus reveals a causal chain of effects from UX on online shop attractiveness, brand attitude and behavioral intentions. Again, explicit and implicit perceptions were considered.

Science and practice are increasingly emphasizing that storytelling emotionalizes content, which facilitates effective communication and builds strong relationships with customers. Little evidence exists about its efficient implementation in an online shopping context and in fulfilling hedonic and pragmatic needs throughout the online journey. This study provides novel insights into managing online shoppers' UX, brand-related perceptions and behavioral intentions with the optimal use of techniques to implement storytelling. Furthermore, this is one of the first studies to holistically consider the human perception of online shops by drawing on theories and methods of psychology, marketing, consumer behavior, brand research and consumer neuroscience and considering explicit and implicit information processing in terms of hedonic and pragmatic UX and brand-related measures.

Digitalization, innovation and changing customer requirements drive the continuous improvement of an organization's business processes. IT demand management (ITDM) as a methodology supports the holistic governance of IT and the corresponding business process change (BPC), by allocating resources to meet a company's requirements and strategic objectives. As ITDM decision-makers are not fully aware of how the as-is business processes operate and interact, making informed decisions that positively impact the to-be process is a key challenge.

In this paper, the authors address this challenge by developing a novel approach that integrates process mining and ITDM. To this end, the authors conduct an action research study where the researchers participated in the design, creation and evaluation of the approach. The proposed approach is illustrated using two sample demands of an insurance claims process. These demands are used to construct the artefact in multiple research circles and to validate the approach in practice. The authors applied learning and reflection methods for incrementally adjusting this study’s approach.

The study shows that the utilization of process mining activities during process changes on an operational level contributes to (1) increasing accuracy and efficiency of ITDM; (2) timely identification of potential risks and dependencies and (3) support of testing and acceptance of IT demands.

The implementation of this study’s approach improved ITDM practice. It appropriately addressed the information needs of decision-makers and unveiled the effects and consequences of process changes. Furthermore, providing a clearer picture of the process dependencies clarified the responsibilities and the interfaces at the intra- and inter-process level.

This exploratory research aims to analyze sustainable innovation in the context of inclusive business in Latin America.

The study performs a summative content analysis of 22 inclusive businesses (IBs) of current Business Call to Action (BCtA) members in Latin America. Codes were created to identify the modification or introduction of sustainable products/services/processes. Data were analyzed using NVivo 12.

Results show a prevalence of Colombian examples within Latin American inclusive business, and a more significant proportion in the agricultural sector, consistent with reports found in the literature. The authors found that sustainable innovation takes place when introducing new products/services/processes that respond to the needs of the bottom of the pyramid (BoP) population, or modifying existing processes and services to make them more sustainable.

As most sustainable innovation literature is product-oriented and technically dominated, these results contribute to the newer works adopting a more comprehensive conception of innovation, providing empirical evidence at the product, service and process levels. The results provide insights on how inclusive businesses make adaptations to improve the sustainability of their supply chains to bring their products/services within reach of isolated and disadvantaged communities. The findings also suggest that sustainable product innovation in an inclusive business goes beyond a cost reduction objective. Tailored design reveals a hybrid socioeconomic goal with a high degree of local context embeddedness and precise attention to nascent specialized demand. The results could be of practical use for organizations that want to operate an inclusive business in BoP markets.

This paper proposes a progressive, multi-level framework for diagnosing maintenance performance: rapid performance health checks of key performance for different equipment groups and end-to-end process diagnostics to further locate potential performance issues. A question-based performance evaluation approach is introduced to support the selection and derivation of case-specific indicators based on diagnostic aspects.

The case research method is used to develop the proposed framework. The generic parts of the framework are built on existing maintenance performance measurement theories through a literature review. In the case study, empirical maintenance data of 196 emergency shutdown valves (ESDVs) are collected over a two-year period to support the development and validation of the proposed approach.

To improve processes, companies need a separate performance measurement structure. This paper suggests a hierarchical model in four layers (objective, domain, aspect and performance measurement) to facilitate the selection and derivation of indicators, which could potentially reduce management complexity and help prioritize continuous performance improvement. Examples of new indicators are derived from a case study that includes 196 ESDVs at an offshore oil and gas production plant.

Methodological approaches to deriving various performance indicators have rarely been addressed in the maintenance field. The proposed diagnostic framework provides a structured way to identify and locate process performance issues by creating indicators that can bridge generic evaluation aspects and maintenance data. The framework is highly adaptive as data availability functions are used as inputs to generate indicators instead of passively filtering out non-applicable existing indicators.

The purpose of this paper is to progress operations management theory and practice by organising contributions to knowledge production, in industrial sustainability, from disparate researcher communities. It addresses the principal question “What scholarly dialogues can be explicated in the emerging research field of industrial sustainability?” and sub-questions: what are the descriptive characteristics of the evidence base? and what thematic lines of scientific inquiry underpin the body of knowledge?

Using an evidenced-based approach, a systematic review (SR) of 574 articles from 62 peer-reviewed scientific journals associated with industrial sustainability is conducted.

This paper distinguishes three prevailing dialogues in the field of industrial sustainability, and uses Kuhn’s theory of paradigms to propose its pre-paradigmatic scientific status. The three dialogues: “productivity and innovation”, “corporate citizenship” and “economic resilience” are conjectured to privilege efficiency strategies as a mode of incremental reductionism. Industrial sustainability espouses the grand vision of a generative, restorative and net positive economy, and calls for a future research trajectory to address institutional and systemic issues regarding scaling-up and transition, through transformative strategies.

The review is limited by the nature of the inquiries addressed in the literatures by specific researcher communities between 1992 and 2014.

This study performs the first SR in the field of industrial sustainability, synthesises prevailing scholarly dialogues and provides an evaluation of the scientific status of the field.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.