International Journal of Innovation and Technology Management

The paper’s goals are to comprehend strategies for tourism destinations after the coronavirus. The research question (RQ) is if the digital platform experience of a leading country in wine tourism can help to overcome COVID-19 and to turn the sector. The general topics related to destinations, specifically Italian wine tourism destinations, have been elaborated on in the introduction. Starting with a literature review relating to the destination tourism crisis in the tourism sector, the paper highlights the potential and basic lessons for coping with the current crisis. The method, which is connected to a wine tourism destination in Italy, emphasizes both qualitative and quantitative approaches. The results demonstrate the best practices as well as the bottlenecks. The discussions would result in the creation of strategic alternatives specific to the sector and its destinations. The study limits, considering bottlenecks that might arise in the future. The findings emphasize that the sector requires substantial funding from information and communication technology (ICT) to build smart destinations.

The COVID-19 pandemic and social distancing entangled physical trading of products and services worldwide. As a result, the Commercial and Industrial Association of Marília (ACIM) developed and provided businesses with a marketplace platform called “Marília.Dakki.” In this context, knowledge emerged as a resource, and knowledge sharing became a fundamental activity for the marketplace implementation. Thus, the objective of the research was to identify and analyze the influential aspects of knowledge sharing (IAKS) in “Marília.Dakki.” The research is characterized as qualitative and exploratory and used the case study method. Questionnaires were used to acquire data from the 19 subjects involved in the “Marília.Dakki” operations, as well as an interview with the Director of IT and Innovation. As a result of the research, people, processes, and culture were identified as IAKS, and these aspects, when related, generated nine other IAKS. The researchers concluded that these IAKS found in the research impacted the marketplace adoption, in addition to its maintenance as a collaborative environment, and are of great importance for the survival and development of companies, both during the pandemic and after it.

Among generic technology management activities, rapid technology identification and selection stand as the significant determinants of technology adoption success in the digital transformation era. Especially for manufacturing SMEs in developing countries, rapid digital technologies are critical since they struggle to protect their competitiveness in global value chains threatened by digitalization. Previous studies introduce various multi-criteria decision-making model-based approaches to identify and select appropriate manufacturing technologies. However, these approaches were relatively rigid and required an advanced understanding of the technology for criteria and alternative settings and evaluation. Decision-makers need more flexible and scalable contextual frameworks for technology selection in digitalization. Since digital technologies offer both benefits and challenges, the decision-making models should reflect this dialectic nature of Industry 4.0 adoption and contextually optimize their decisions by combining multiple quantitative methods for technology identification and selection. Besides, case studies on digital technology selection are rare in manufacturing SMEs from developing country context in the literature. In this context, this study proposes a technology selection framework that utilizes the three dimensions (industry 4.0 technologies, benefits, and challenges) and combines AHP with a QFD-inspired intervention matrix and an optimization model by Mixed Integer Programming (MIP). The proposed model is validated with a case study from the automotive supplier industry in Turkey with the data provided from interviews and a Delphi survey with 11 experts from the digitalization value chain of the selected industry. Case study results revealed that the highest benefits of industry 4.0 lie in process/quality efficiency improvement and reduced inventory. At the same time, data analytics and sensor technologies occurred as the most critical tools. Significant challenges of digital technology adoption are insufficient expert know-how and budget constraints.

This study explores the short- and long-term expectations about adoption of conversational agents in the organizational frontline. Drawing from in-depth interviews with managers and developers in organizations that have implemented these agents, it sheds light on how the deployment of and collaboration with technology-based autonomous agents influences service activities, and expectations of changes in organizational processes. The interviews revealed that implementations are done on a rather iterative and experimental basis, often balancing the current limits of technology while aiming at improved efficiency, augmenting the work of frontline employees, and meeting the ever-growing demands from consumers.

Virtual assistants are becoming significant in the area of voice commerce. Voice commerce creates an environment where orders and payments can be done through voice recognition, increasing its accessibility in comparison to other existing commercial transaction methods. Thus, the field is expected to grow into a promising industry. However, the full bloom of voice commerce depends on user acceptance, as well as technological improvement. This study develops a conceptual framework to describe factors influencing user acceptance to voice commerce, which are analyzed with the structural equation model by combining the technology acceptance model (TAM) and the model of innovation resistance (MIR). With accuracy, social presence, and interactivity of a virtual assistant, along with user attributes such as user innovativeness and experience, as variables, a survey of 151 Koreans in their 20s and 30s is conducted. Moreover, the impact of three factors, relative advantage, perceived ease of use, and perceived risk, on innovation acceptance and resistance is analyzed to find key variables that affect the resistance to and acceptance of voice commerce. These findings provide notable implications to companies currently using voice commerce platforms and guidance to an emerging commercial trading system.

The study investigates how the alignment at the processing levels between information systems (IS) strategy, through strategy-as-practice approach, and innovation influences corporate performance (CP) under environmental uncertainty from 856 Brazilian firms by PLS-SEM. The results indicated that all approaches of alignment between IS strategy and innovation have strong influences on CP. The alignment with ambidextrous innovation had a 62% higher contribution on CP than alignment between exploitative innovations. Additionally, exploitative innovations had positive effects on CP under high hostility environments; and explorative and ambidextrous innovations had positive large and strong effects on CP under high dynamic environments.

The problem of process models in engineering change management is their static approach, which hinders enterprises from using them in daily business. The SECPON process is a standardized implementation process for engineering changes with the additional benefit of enabling users to adjust this process according to the specific requirements of their company and product. The indication that there are influencing factors on change processes is innovative for the theory of engineering change management. Additionally, special process steps for certain branches, such as the food industry, the pharmaceutical industry, the aeronautical industry, and the railway industry, are integrated. Due to the wide variety of literature and survey participants, the reference process is universally applicable. The deductive–inductive research results enable business users to apply more accurate and structured engineering change processes. Researchers profit from the successful new approach to engineering change management with the adaptive process model.

Usability is an emerging subject for smartphone design and service, which results in the overall quality and achievement of a product and allows users to perform various tasks. In this context, this study aims to propose an integrated smartphone usability framework for higher service level and user experience with a causal analytic approach. Involving tested relationships with theoretical concerns a conceptual usability assessment model is proposed including design, customer focus, quality, innovation, usability, and user perception variables. The provided model is developed using the Bayesian neural networks based universal structure modeling (USM) method. The reliability and validity are empirically tested for the questionnaire data collected from 1068 smartphone users. The results and findings showed that design, customer focus, quality, and innovation explain usability, and user perception as an ultimate variable is interpreted by usability. Also, strategic, and valuable information for smartphone designers and marketing people to understand user perceptions for smartphone usability is provided.