Search results

Digitalization is changing the assets, competencies, and value creation of the customer insight function. New data sources, methods, and technologies provide an unprecedented wealth of data and opportunity for efficiency. At the same time, it is leading to an evolution in necessary capabilities such as data synthesis, networking, and constant learning. Changes in the means of value creation have included automation of insights, more frequent evaluation of business results, and more emotional inspiration. Customer insights in the machine age drive customer centricity and go beyond the descriptive research function of previous “market research” within companies.

To identify and cite examples of critical tactics for implementing Porter's generic strategies.

A survey of over 200 organizations was conducted to determine their relative use of tactics and organizational performance. Factor analysis and regression analyses were used to identify tactics that were strongly related to organizational performance. Examples of implementation are presented to illustrate use of the critical tactics.

A list of ten tactics were identified as significantly related with the generic strategies and higher levels of organizational performance.

As is typical with survey research, the convenience sample of organizations used in this survey may or may not be representative of all organizations. Also, when using regression analysis it is important to keep in mind that correlation does not necessarily mean causation. Therefore we are not certain that the significant tactics caused the higher levels of organizational performance.

Managers will gain the knowledge of how to better tailor their strategy implementation to more effectively implement whatever generic strategy they attempt to use. Managers should pay particular attention to the critical tactics associated with their generic strategy.

This article is a practitioner‐oriented translation of an academic research study. The value of the current article is to share our findings with a more practitioner‐oriented community and present the implications of our findings to managers and decision‐makers in a less technical format.

Following a contingency approach, this paper aims to understand when service automation can enhance or destroy value for customers in the frontline by (1) providing a comprehensive overview of factors that influence the value co-creation/co-destruction potential of service automation and (2) zooming in on the combination of service contexts and service tasks to develop research propositions.

This paper uses a grounded theory approach based on qualitative data from multiple methods (i.e. a diary study with follow-up interviews, a consultation of academic experts and a storyboard study) as well as a systematic literature review to develop (1) a Framework of Automated Service Interactions (FASI) and (2) a contingency model for service tasks/contexts.

This paper presents a framework which gives an overview of factors influencing the value co-creation/co-destruction potential of service automation. The framework discerns between three types of factors: service design (i.e. controllable and manageable by the organization), static contingency (i.e. uncontrollable and fixed) and dynamic contingency (i.e. uncontrollable and flexible). Furthermore, the paper presents a contingency model based on the combination of service contexts and service tasks which results in seven research propositions.

This paper brings structure in the fragmented field of service automation. It integrates and summarizes insights regarding service automation and sheds more light on when service automation has the potential to create or destroy value in the organizational frontline.

Purpose: The purpose of this chapter is to review and critically evaluate robots, artificial intelligence and service automation (RAISA) applications in the restaurant industry to educate professors, graduate students, and industry professionals.

Design/methodology/approach: This chapter is a survey of applications of RAISA in restaurants. The chapter is based on the review of professional and peer-reviewed academic literature, and the industry insight section was prepared based on a 50-minute interview with Mr. Juan Higueros, Chief Operations Officer of Bear Robotics.

Findings: Various case studies presented in this chapter illustrate numerous possibilities for automation: from automating a specific function to complete automation of the front of the house (e.g., Eatsa) or back of the house (e.g., Spyce robotic kitchen). The restaurant industry has already adopted chatbots; voice-activated and biometric technologies; robots as hosts, food runners, chefs, and bartenders; tableside ordering; conveyors; and robotic food delivery.

Practical implications: The chapter presents professors and students with a detailed overview of RAISA in the restaurant industry that will be useful for educational and research purposes. Restaurant owners and managers may also benefit from reading this chapter as they will learn about the current state of technology and opportunities for RAISA implementation.

Originality/value: To the best of the authors’ knowledge, this chapter presents the first systematic and in-depth review of RAISA technologies in the restaurant industry.

Service managers are continually challenged with balancing customer demand and service capacity. Recent studies have raised awareness of various demand and capacity management practices available to services, but little numerical work has been done to identify how these decisions work together and how they relate to one another. For instance, reducing prices may attract customers during a slow period, but the extent of impact this should have on cross‐training staff is not clear. A simulation based on theoretical and empirical insights explores the impact of various decisions on profitability and operations. The decisions modelled include the impact of: automation, customer participation, cross training employees, informing customers about the operation, and others. It is shown that demand and capacity decisions do indeed impact on each other – sometimes in ways that are not initially obvious. Results provide useful thought‐starters for service managers striving to improve their operations.

Integrating artificial intelligence (AI) into various industries, including the financial sector, has transformed them. This paper aims to examine the influence of integrating AI, including machine learning, process automation, predictive analytics and chatbots, on financial institutions and explores its various aspects and areas. The study aims to determine the impact of AI integration on financial services, products and customer experience.

The research study uses quantitative and qualitative methods, as well as secondary data analysis. It investigates four AI subfields: machine learning, process automation, predictive analytics and chatbots.

The research findings indicate that integrating AI, particularly in machine learning and chatbot subfields, holds promise and high strategic potential for financial institutions. These subfields can contribute significantly to enhancing financial services and customer experience. However, the significance of predictive analytics integration and process automation is relatively lower. Although these subfields retain their usefulness, they might necessitate alternative workflows and tools that incorporate human involvement. Overall, AI integration minimizes human interactions and errors in financial institutions.

The research study contributes original insights by exploring the specific subfields of AI within the financial industry and assessing their strategic significance. It provides recommendations for financial institutions to adopt AI integration partially in multiple phases, measure and evaluate the impact of the transformation and structure internal units and expertise to strategize adoption and change.

The paper aims to fill this gap by positing a framework that considers the service automation decision as a matter of knowledge management: a choice between human resident and codified knowledge assets.

The paper is a conceptual paper, grounded in the knowledge-based view.

The paper uses the information processing theory, which argues that the level of uncertainty in a process should dictate the type of knowledge deployed, as the contingency for the automation choice, and customer interaction uncertainty as the driver of that contingency. From these ideas, propositions are generated relating customer interaction uncertainty and service automation. Further implications for artificial intelligence (AI) are also explored.

The framework illuminates and informs the strategic choices regarding service automation, including the use of AI in professional services, a timely and highly important topic. It offers a valuable model for practitioners and contributes to the academic literature by pointing the way for future directions for scholarly research.

To meet customers' expectations on shorter lead times, high product availability, flexibility, and variation in delivery and return options, retailers have turned their attention to warehousing and are making big investments in technology. Currently, technology providers are pushing for smart warehousing, a new and under-researched phenomenon. This study aims to conceptualize the term and examine pathways toward implementing smart warehousing.

An exploratory survey was administered to 50 leading Swedish retailers in varying segments. A two-tailed t-test for equality of means was used to detect significant differences between current and future states.

The study found that future smart warehouses will be automated, autonomous, digital, and connected, but that retailers will follow different paths along this journey, driven by contextual trends, e.g. sales growth, wider product assortment, shorter lead-time offerings, and integration of brick-and-mortar and online stores. Interestingly, the study revealed that many of the retailers that aim to create smart warehouses in five years are not the retailers with the most developed technology today.

The paper operationalizes smart warehousing in two dimensions: degree of automation and degree of digitalization and connectivity of information platforms. Based on the findings, 16 theoretical propositions are put forth that, based on contextual factors, explain different pathways for retailers to implement smart warehousing.

The empirical insights and theoretical discussions provide practically useful guidance, including outlined trends, for selecting and benchmarking automation and complementary technologies in warehouse operations.

This paper conceptualizes and operationalizes smart warehousing – an original approach. It is also one of the first to investigate the technological transformation in retail warehousing empirically, explaining how and why retailers choose different pathways toward smart warehousing.

The enabling technologies that emerged from information technology (IT) have had a considerable influence upon the development of marketing tools, and marketing has become digitalized by adopting these technologies over time. The purpose of this paper is to demonstrate the impacts of these enabling technologies on marketing tools in the past and present and to demonstrate their potential future. Furthermore, it provides guidance about the digital transformation occurring in marketing and the need to align of marketing and IT.

This study demonstrates the impact of enabling technologies on the subsequent marketing tools developed through a content analysis of information systems and marketing conference proceedings. It offers a fresh look at marketing's digital transformation over the last 40 years. Moreover, it initially applies the findings to a general digital transformation model from another field to verify its presence in marketing.

This paper identifies four eras within the digital marketing evolution and reveals insights into a potential fifth era. This chronological structure verifies the impact of IT on marketing tools and accordingly the digital transformation within marketing. IT has made digital marketing tools possible in all four digital transformation levers: automation, customer interaction, connectivity and data.

The sequencing of enabling technologies and subsequent marketing tools demonstrates the need to align marketing and IT to design new marketing tools that can be applied to customer interactions and be used to foster marketing control.

This study is the first to apply the digital transformation levers, namely, automation, customer interaction, connectivity and data, to the marketing discipline and contribute new insights by demonstrating the chronological development of digital transformation in marketing.

The preceding revolution, Industry 4.0, surfaced by way of the influx of digital and automation technologies. Industry 5.0 followed the suit and the world is on the threshold of this new evolution. Industry 5.0 attempts to bring together the competency of smart machines and the exceptional ingenious potentials of the human workforce. Industry 5.0 is humanizing the digital and automated systems. It recognizes both automated technology and the human innovative skills on an equal platform. Marketing in its new role revolves on the axis of automation and cyber technology of Industry 5.0. This new makeover of marketing processes generates superior marketing actions, restructures marketing workflows, and assesses the results of marketing promotions. Industry 5.0 tools make available a fundamental marketing catalog for all marketing content and communications, thus assisting marketers to fashion a fragmented, customized, and favorable marketing experiences for prospective buyers. These systems and spaces offer automation attributes across numerous phases of marketing including videos, blogs, emails, social media, lead generation, direct mails, digital advertising, and more.

This chapter aims to introduce the concept of Industry 5.0, where robots and machines are interweaved with the human intellect and labor as teammate instead of opponent. The objective of the chapter is to examine and explore the different facets of marketing in the face of Industry 5.0. The chapter describes the challenges and future trends and practices in marketing field in the wake of Industry 5.0 as the way forward for the companies for sustainability and resilience.