Search results
1 – 4 of 4Bernd F. Reitsamer, Nicola E. Stokburger-Sauer and Janina S. Kuhnle
Effective customer journey design (ECJD) is considered a key variable in customer experience management and an essential source of brand meaning and pro-brand behavior. Although…
Abstract
Purpose
Effective customer journey design (ECJD) is considered a key variable in customer experience management and an essential source of brand meaning and pro-brand behavior. Although previous research has confirmed its importance for driving brand attitudes and loyalty, the role of consumer-brand identification as a social identity-based influence in this relationship has not yet been discussed. Drawing on construal level and social identity theories, this paper aims to investigate whether effective journeys and the resulting overall journey experience are equally powerful in driving brand loyalty among customers with different levels of consumer-brand identification.
Design/methodology/approach
The present article develops and tests a research model using data from the European and US service sectors (N = 1,454) to investigate how and when ECJD affects service brand loyalty.
Findings
Across two cultural contexts, four service industries and 33 service brands, the results reveal that ECJD is a crucial driver of service brand loyalty for customers with low consumer-brand identification. Moreover, the findings show that different aspects of journey effectiveness positively impact the valence of customers’ experience related to those journeys – a process that is ultimately decisive for their brand loyalty.
Originality/value
This study is unique because it generates theoretical and practical knowledge by combining the literature streams of customer journey design, customer experience and branding. Furthermore, this work demonstrates that consumer-brand identification is a critical boundary condition to be considered in the relationship between ECJD and brand loyalty in services.
Details
Keywords
Behzad Maleki Vishkaei and Pietro De Giovanni
This paper aims to use Bayesian network (BN) methodology complemented by machine learning (ML) and what-if analysis to investigate the impact of digital technologies (DT) on…
Abstract
Purpose
This paper aims to use Bayesian network (BN) methodology complemented by machine learning (ML) and what-if analysis to investigate the impact of digital technologies (DT) on logistics service quality (LSQ), employing the service quality (SERVQUAL) framework.
Design/methodology/approach
Using a sample of 244 Italian firms, this study estimates the probability distributions associated with both DT and SERVQUAL logistics, as well as their interrelationships. Additionally, BN technique enables the application of ML techniques to uncover hidden relationships, as well as a series of what-if analyses to extract more knowledge.
Findings
This study was funded by the European Union—NextGenerationEU, in the framework of the GRINS-Growing Resilient, INclusive and Sustainable project (GRINS PE00000018—CUP B43C22000760006). The views and opinions expressed are solely those of the authors and do not necessarily reflect those of the European Union, nor can the European Union be held responsible for them.
Originality/value
This research delves into the influence of DTIE and DTA on SERVQUAL logistics, thereby filling a gap in the existing literature in which no study has explored the intricate relationships between these technologies and SERVQUAL dimensions. Methodologically, we pioneer the integration of BN with ML techniques and what-if analysis, thus exploring innovative techniques to be used in logistics and supply-chain studies.
Details
Keywords
Jorge Sanabria-Z and Pamela Geraldine Olivo
The objective of this study is to propose a model for the implementation of a technological platform for participants to develop solutions to problems related to the Fourth…
Abstract
Purpose
The objective of this study is to propose a model for the implementation of a technological platform for participants to develop solutions to problems related to the Fourth Industrial Revolution (4IR) megatrends, and taking advantage of artificial intelligence (AI) to develop their complex thinking through co-creation work.
Design/methodology/approach
The development of the model is based on a combination of participatory action research and user-centered design (UCD) methodologies, seeking to ensure that the platform is user-oriented and based on the experiences of the authors. The model itself is structured around the active and transformational learning (ATL) framework.
Findings
This study highlights the importance of addressing 4IR megatrends in education to prepare students for a technology-driven world. The proposed model, based on ATL and supported by AI, integrates essential competencies for tackling challenges and generating innovative solutions. The integration of AI into the platform fosters personalized learning, collaboration and reflection and enhances creativity by offering new insights and tools, whereas UCD ensures alignment with user needs and expectations.
Originality/value
This research presents an innovative educational model that combines ATL with AI to foster complex thinking and co-creation of solutions to problems related to 4IR megatrends. Integrating ATL ensures engagement with real-world problems and critical thinking while AI provides personalized content, tutoring, data analysis and creative support. The collaborative platform encourages diverse perspectives and collective intelligence, benefiting other researchers to better conceive learner-centered platforms promoting 21st-century skills and co-creation.
Details
Keywords
This study aims to explain the effects of different types of innovations on organizational performance in terms of firms’ external effectiveness and internal efficiency. The study…
Abstract
Purpose
This study aims to explain the effects of different types of innovations on organizational performance in terms of firms’ external effectiveness and internal efficiency. The study examines the interrelationship of technical and nontechnical innovations in complex services and the mediating effect of customer participation on the relationship between innovation type and organizational performance.
Design/methodology/approach
The study draws on a neo-Schumpeterian model for innovation to examine the complex service setting of healthcare provision. Data from Statistics Sweden, containing 38 hospitals and 242 primary care units in Sweden, provided the study's results.
Findings
The findings show the importance of combining different types of innovations in complex services, demonstrating a mediating effect of nontechnical innovation on both the relationship between technical innovations and external effectiveness and internal efficiency. Moreover, the results show that customer participation has a positive mediating effect for technical innovation and nontechnical innovation on external effectiveness. However, there is no such significant effect on internal efficiency.
Research limitations/implications
The findings are based on self-assessment data, which has inherent limitations. The innovation data used were cross-sectional, which may lack reliability (although self-assessed data counter this risk to some extent).
Practical implications
Managers should pursue both technical and nontechnical innovations for gains in external effectiveness and internal efficiency. However, complex services call for technical innovations to be accompanied by nontechnical innovations to support positive effects. The results cause a dilemma for managing customer participation in complex services. As the results show customer participation resulting in external effectiveness, they also fail to establish an effect on internal efficiency.
Originality/value
The primary contribution is to add to the knowledge of different types of innovation in complex services by demonstrating their interdependent effects on both external effectiveness and internal efficiency. Furthermore, the study tests and advances the mediating effect of customer participation in complex services on organizational performance.
Details