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This paper aims to answer questions pertinent to whether or not services provided by smart hotels are really what customers are looking for, as well as to ascertain what are some unintended experiences guests may encounter. In essence, to the best of the authors’ knowledge, this research is the first in the field to acknowledge the paradox of smart service.

This inquiry adopts a qualitative approach with data-driven from online customer reviews and semistructured interviews. Thematic analysis was undertaken to interpret review comments.

Results point to a new phenomenon, which is coined as the smartness paradox. In particular, customers on one hand enjoy an array of smart-infused experiences that jointly offer patrons a sense of a futuristic lifestyle. On the other hand, smart devices superimpose a number of hindrances that bring guests dismay and annoyance.

This investigation brings smart service failure to the fore to highlight several key failure themes that could jeopardize the entire operation with debased customers’ satisfaction and loyalty inclination.

The smartness-paradox framework used in the present inquiry entails both approach and avoidance consequences customers enact depending on their smart experiences.

Advances in autonomous technology have transformed customer experience. Most prior research has investigated the effect of augmented reality (AR) on purchase intention, yet few research has discussed the effect of semiautonomous AR in the context of service use. Semiautonomous AR recognizes content in the present reality, inserts and adjusts virtual content, supervises the users and enables them to feel in control of the virtual content overlaid in observed reality resulting in enriched user experience and thereby augmentation experience. This research demonstrates how perceived control of virtual content leads to higher perceived augmentation experiences among semiautonomous AR users than among non-AR users. In addition, this research examines the mediation effects of enriched user experience and perceived augmentation experience on user satisfaction and users’ willingness to continue using AR. Results also indicate that AR users perceive a higher augmentation experience than non-AR users. However, users’ willingness to continue using AR is not significantly different between AR and non-AR users.

This study derives six hypotheses and uses a preliminary study, a field study and a lab study to evaluate the hypotheses. A field study was conducted in a car dealership to test the hypotheses, and a lab experiment was conducted in a controlled setting to corroborate the results obtained in the field study and test the underlying causal effects.

Semiautonomous AR can constantly sense, plan and not necessarily always act over the virtual content to sustain the interaction with its users. Perceived control of virtual content enhances perceived augmentation experience, and its effect of perceived control of virtual content on perceived augmentation experience is higher among semiautonomous AR users than among non-AR users. Perceived control of virtual content is a key to enriched user experience, augmentation experience and thereby users’ attitude and behavior. In addition, results showed that enriched user experience mediates the effect of perceived control of virtual content on perceived augmentation. User satisfaction mediates the effect of perceived augmentation experience on users’ willingness to continue using AR. The theoretical and practical contributions are comprehensively discussed.

Some limitations of the studies are ascertained. First, a larger sample size might be required to achieve generalizability and a strong test of the applied theory. Second, new field studies can reflect customers’ real attitudes and behaviors so as to reveal realistic interactions between the device properties and the human will in solving actual problems. The user is interested in participating in the solution within the sensing-planning-acting process as depicted by this research. Third, new research to test AR’s capabilities in bounded and symbiotic conditions can illustrate the level of autonomy each type requires, providing additional insights into why supervised AR autonomy best reflects semiautonomous AR. The pioneering structural model offered in this study (perceived control of virtual content-perceived augmentation experience-users’ satisfaction-users’ willingness to continue using AR) should be tested with new samples in other industries, aside from including other variables that may enrich the model and increase its explanatory power. In addition, future research might use other AR devices such as smart glasses to explore the effects of AR on perceived control of virtual content, enriched user experience and perceived augmentation experience. Future studies can investigate the effect of auditory and visual augmentation on enriched user experience and perceived augmentation experience, and involve features of artificial intelligence (AI) to assist users in decision-making. Regarding context, this research showed that age and gender differences did not affect the results. Nonetheless, age and gender, and perhaps additional demographic characteristics, may concern future studies.

Some recommendations for technology developers are derived from this research. AR is revolutionizing service experience. As technologies are becoming autonomous, developers seek ways to design experiences to enhance consumers’ sense of control over their interaction with such systems. Companies cannot create customer experience (Becker and Jaakkola, 2020), yet they can leverage the level of autonomy in AR to sustain ongoing interaction with customers. It is vital to design an autonomous AR that focuses on users’ needs, desires and well-being (de Bellis and Johar, 2020) that drive novel experiences (Novak and Hoffman, 2019). This study recommends AR developers design autonomous features in AR that enable customers to interact with the virtual contents generated by AR and extend their own capabilities to perform a task and feel expanded. While designing a fully autonomous system may hinder users to feel in control of their choice (Schmitt, 2019), service companies can develop an AR system that sustains an interaction, involves the user in value co-creation and guides the user (Alimamy and Gnoth, 2022). AR can sustain an interaction with the users by continuously scanning the objects in the reality and providing sensory feedback such as product size recommendations (e.g. eyeglasses) that facilitate customers’ information processing (Poushneh, 2021b; Heller et al., 2019). To achieve this, developers may focus on technology qualities such as “image recognition,” a subset of AI. With image recognition, AR can effectively provide instruction as if the customer is in a real setting. The proper incorporation of image recognition in the design of AR while enabling users to interact with 3D virtual images sustains their interaction with AR and makes them feel in control of their interaction with AR. Service companies need to ensure users feel in control of their interaction and expand their capacities to engage in the service experience with AR to accomplish their desired tasks. AR’s capacities enable users to expand their abilities to fix their basic service problems without referring to or speaking to a service provider agent in a service context. Therefore, instead of taking their car back to the dealership, customers can use AR mobile applications or glasses provided by car manufacturers to learn and fix basic vehicle problems.

This research advances the marketing literature on how users feel in control of virtual content when they interact with a semiautonomous AR that subsequently influences enriched user experience, perceived augmentation experience, attitudes and behavior.

This study aims to design a facility network for the weavers to do direct business in the Indian handloom industry by using tourists as potential customers.

Data from 4,001 weavers of the handloom industry and 82 tourist locations of Varanasi city were collected. This data was analysed using the k-mean and elbow methods to determine the locations and the optimal number of collection centres, selling stores and warehouses to provide opportunities for the weavers to do direct business.

The study's findings showed that a greater opportunity could be provided with four optimal collection centres and selling stores, along with two warehouses in the handloom industry of Varanasi city. These results provide valuable guidance for policymakers to plan the Varanasi handloom network of facilities efficiently and effectively to improve the conditions of weavers.

Determining the optimal locations is crucial for designing a facility network. The proposed network will aid the government and policymakers in comprehending and pinpointing potential sites to establish new facilities in the handloom industry in Varanasi, a city with tourism potential.

The retail landscape is dramatically changing due to a series of socio-economic and technological challenges, which can be faced through the adoption of smart technologies. Accordingly, a significant number of publications in this field have been produced, albeit with fragmented results. Therefore, this paper aims at both providing a clear and organised overview of the main smart technologies for physical retailing, in terms of application fields and expected impact, while identifying the major shortcomings and future research avenues.

The research conducts a systematic review of the literature concerning the assimilation of smart technologies within physical retail environments, resulting in the analysis of 103 papers published from 2005 to 2023. The review highlights (1) the main smart technologies employed in retail stores, (2) their application area and (3) the beneficiaries of their adoption. Accordingly, these three aspects are initially assessed independently and then examined in combination.

The analysis presents a comprehensive list of 16 key technologies (what) that can support a wide range of processes, spanning from back-end functions to front-end activities, also enabling the connection with online channels (where), catering several and different benefits (why) to both customers and retailers (who). Besides, the research points out many uncovered topics that could be addressed by the academic community.

To the best of the authors’ knowledge, the review is the first one in the literature offering a thorough and organised overview of the different available technologies for in-store application and their impact on physical retail processes.

To explore the mechanisms of the implementation strategy, “oilcloth sessions” and understand and explain the ripple effects of oilcloth sessions as a strategy to implement a new emergency department.

A qualitative design was used whereby data were collected using field notes from an ethnographic study of the oilcloth sessions and follow-up semi-structured interviews with staff, managers and key employees who participated in the oilcloth sessions. The data analysis was inspired by the realist evaluation approach of generative causality proposed by Pawson and Tilley.

The primary ripple effect was that the oilcloth sessions were used for different purposes than the proposed program theory, including being used as: (1) a stage, (2) a battlefield, (3) a space for imagination and (4) a strategic management tool influencing the implementation outcomes. The results bring essential knowledge that may help to explain why and how a well-defined implementation strategy has unplanned outcomes.

Unintended outcomes of implementation strategies are an underexplored issue. This study may help implementation researchers rethink the activities required to reduce unintended negative outcomes or explore potential unplanned outcomes and, in this way, hinder or enhance outcomes, effectiveness and sustainability. Future studies within implementation research should incorporate attention to unintended outcomes to fully understand the impact of implementation strategies.

This paper aims to introduce the experience-dominant (Ex-D) logic model, which synthesizes the creation, perceptions and outcomes of Ex-D logic. It is designed to offer valuable insights for strategic managerial applications and future research directions.

Employing a qualitative approach by using eight selected product launch events from reviewed 100 event videos and 55 in-depth interviews with industrial managers to develop an Ex-D logic model, and data were coded and analysed via NVivo.

Results show that the firm’s Ex-D logic is operationalized as the mentalizing of the three types of customer needs (service competence, hedonic excitations and meaning making), the materializing of three types of customer experiences and customer journeys (service experience, hedonic experience and brand experience) and the moderating of three types of customer values (service values, hedonic values and brand values).

This study has implications for adding new insights into existing theory on dominant logic and customer experience management and also offers actionable recommendations for managerial applications.

This study sheds light on the importance of Ex-D logic from a strategic point of view and provides an organic view of the firm. It distinguishes firm perspective from customer perspective, firm experience from customer experience and firm journey from consumer journey.

COVID-19 is one of people's glooming disasters that brought the entire world to a standstill. To reduce the effect, a countrywide lockout was announced. Stock and distribution chains were affected on a larger scale. Due to the pandemic, purchasing habits of people have changed. It is also evident that individuals are choosing to shop online. As per recent researches, consumer buying behaviour has transformed as a result of the contagion. Due to which, many businesses are revolutionizing to adjust to the new reality. This study was taken up to scrutinize the effect of Corona Virus Disease of 2019 on changes in customer buying behaviour towards E-commerce. This study has offered detailed information on new ways of buyer shopping. It suggests that during the COVID-19 pandemic, consumers have become more accepting of internet shopping, experts in webrooming and with time they are mastering the art of online shopping as well as tuned to online payment methods and are accepting to live with ease in an economy of cashless e-transactions.

This paper aims at understanding how automotive firms integrate customer relationship management (CRM) tools and big data analytics (BDA) into their marketing strategies to enhance total quality management (TQM) after the coronavirus disease (COVID-19).

A qualitative methodology based on a multiple-case study was adopted, involving the collection of 18 interviews with eight leading automotive firms and other companies responsible for their marketing and CRM activities.

Results highlight that, through the adoption of CRM technology, automotive firms have developed best practices that positively impact business performance and TQM, thereby strengthening their digital culture. The challenges in the implementation of CRM and BDA are also discussed.

The study suffers from limitations related to the findings' generalizability due to the restricted number of firms operating in a single industry involved in the sample.

Findings suggest new relational approaches and opportunities for automotive companies deriving from the use of CRM and BDA under an overall customer-oriented approach.

This research analyzes how CRM and BDA improve the marketing and TQM processes in the automotive industry, which is undergoing deep transformation in the current context of digital transformation.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

This paper aims to identify and report the differential effects of activity control and capability control on role stressors, which subsequently affect salespeople’s job satisfaction and sales performance.

Drawing on job demands-resources (JD-R) theory, the authors defined active control and customer demandingness as the job demands and capability control as the job resource, and designed their relationship with role stressors, which are indicated as role ambiguity, role conflict and role overload. The authors enrolled a sample of 223 industrial salespeople from pharmaceutical companies. After collecting the data, the authors used structural equation modeling using AMOS to test and estimate causal relationships along with a two-step approach to examine the interaction effect. The authors have also tested the simple slope of two-way interactions. All of the measured variables were identical to those used in previous studies.

The study findings indicate that behavior-based control can be counterproductive. Reducing activity control can decrease role stress, increase job satisfaction and improve job performance; increasing capability control, however, can reduce role stress and increase job satisfaction and performance. It is also important to acknowledge the external environment of the sales context in which behavior-based control is most effective: whereas high customer demandingness and capability control are related to reduced role stress, high customer demandingness and activity control are related to increased role stress.

Sales managers should recognize that different control management regimes reinforce or mitigate salespeople’s job stressors and outcomes under specific conditions (i.e. work environments marked by higher or lower customer demandingness).

Drawing on JD-R theory, the research shows that a behavior control (i.e. activity control and capability control) has differential, and even opposite, psychological consequences.