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This papers aims to study lattice structures in terms of geometric variables, manufacturing variables and material-based variants and their correlation with compressive behaviour for their application in a methodology for the design and development of personalized elastic therapeutic products.

Lattice samples were designed and manufactured using extrusion-based additive manufacturing technologies. Mechanical tests were carried out on lattice samples for elasticity characterization purposes. The relationships between sample stiffness and key geometric and manufacturing variables were subsequently used in the case study on the design of a pressure cushion model for validation purposes. Differentiated areas were established according to patient’s pressure map to subsequently make a correlation between the patient’s pressure needs and lattice samples stiffness.

A substantial and wide variation in lattice compressive behaviour was found depending on the key study variables. The proposed methodology made it possible to efficiently identify and adjust the pressure of the different areas of the product to adapt them to the elastic needs of the patient. In this sense, the characterization lattice samples turned out to provide an effective and flexible response to the pressure requirements.

This study provides a generalized foundation of lattice structural design and adjustable stiffness in application of pressure cushions, which can be equally applied to other designs with similar purposes. The relevance and contribution of this work lie in the proposed methodology for the design of personalized therapeutic products based on the use of individual lattice structures that function as independent customizable cells.

Since the outbreak of the Covid-19 pandemic, many restaurants and catering businesses have introduced or improved online food ordering and delivery services (OFODSs). This study aims to identify service quality expectations about OFODSs, to examine their content and to suggest management strategies to meet these expectations.

Adopting a qualitative method, four focus groups were conducted amongst Italian users of OFODSs.

The results reveal three dimensions of expectations, each comprising two categories that can be set along a continuum: (1) basicness of expectations (ranging from implicit to explicit), (2) accuracy of expectations (ranging from fuzzy to precise) and (3) attainability of expectations (ranging from realistic to unrealistic). Content may refer to technical, social, economic, legal and technological aspects. To meet customer expectations, the following strategies are suggested: customer reassurance, flexibility, continuous improvement, customer education, adaptation to customers' requirements and monitoring of exceptions.

This study provides specific activities in which restaurants and catering businesses could invest to enact the management strategies that emerged from the analysis.

This paper proposes a new classification of expectations and framework for improving OFODS quality by managing customer expectations.

This study aims to explore how manufacturing firms master customer lock-in through value creation by servitization innovation strategies from the perspective of asset specificity.

A multiple case study with triangulation fashion is adopted to identify servitization innovation strategies. Several manufacturing firms were investigated, which are distributed in different positions of the value chain. Content analysis and abductive approaches are adopted to analyze the data. Moreover, an in-depth interview and participatory observation were conducted to refine the analysis results.

This study identified four different focusing points of servitization operations. Based on these, the paper further induces an innovative servitization strategy matrix of customer lock-in, concerning communion, intellectual, existential and insubstantial strategies. Furthermore, a conceptual model of customer lock-in by servitization innovation from the perspective of asset specificity is elaborated. It is suggested that companies can use tangible or intangible resources by sharing or storing operations to create servitization value.

This study theoretically proposes a conceptual model to extend servitization innovation as an intangible asset and adopt the new perspective of asset specificity to illustrate the value creation in servitization to generate customer lock-in.

This study is intended to motivate and guide future researchers to rethink and update their theories of operational capability development. By examining the extensive body of research on operational capabilities and working closely with an industry partner, the authors are iteratively developing new thinking about why our existing models seem to be failing and what aspects are likely to be useful in updating them.

This pathway paper is based on observations gained through a structured literature review, close collaboration with an industry partner and discussions with other industry partners and executives.

The authors identify ways in which the operations management community could begin to challenge and expand existing models of operational capability development. They provide reflections on the network structure of operational capabilities, i.e. their interconnectedness and interactions, which are likely to evolve dynamically over time and have not yet been part of the authors’ thinking about operational capability development.

The authors hope to stimulate new research through this pathway paper. By synthesizing their existing knowledge of operational capabilities and collaborating with an industry partner, the authors have attempted to highlight their limited knowledge of capability development. In addition, the authors offer several opportunities to rethink their existing models.

This study aims to increase understanding of factors influencing the international marketing (IM) strategy of products from emerging markets (EMs) to international markets.

This study conducted case studies by collecting qualitative data through semistructured interviews with respondents from four food product companies in Bangladesh.

This study finds that the firms employ local Bangladeshi people who are knowledgeable in the company culture. They strategically focus on countries where the Bangladeshi diaspora lives and initially target them, approaching natives later. They adapt and customize products to the importers’ requirements to make them visible and increase understanding between product providers and local customers. The findings show that EM firms encounter a mentality that poor countries produce poor quality products; this mindset makes the internationalization of their business difficult.

This research contributes to international product marketing of EM firms by constructing a model of a modern people-oriented marketing strategy for food products. This study contributes to literature on culture by illustrating that the cultural dimensions of collectivism and uncertainty avoidance enhance the development of networks and trust and impact marketing strategy.

This study theorizes the importance of context and an innovation-driven modern people-oriented IM strategy that adapts to customers’ preferences for food products and emphasizes the contribution of diaspora. This research reveals that Bangladeshi firms face challenges both because customers link the country and the companies to low-quality products and because governmental regulations prevent them from establishing a local presence in other countries. This study analyzes challenges EM firms face in the process of IM and the factors affecting Bangladesh in particular.

Algorithm bias refers to repetitive computer program errors that give some users more weight than others. The aim of this article is to provide a deeper insight of algorithm bias in AI-enabled ERP software customization. Although algorithmic bias in machine learning models has uneven, unfair and unjust impacts, research on it is mostly anecdotal and scattered.

As guided by the previous research (Akter et al., 2022), this study presents the possible design bias (model, data and method) one may experience with enterprise resource planning (ERP) software customization algorithm. This study then presents the artificial intelligence (AI) version of ERP customization algorithm using k-nearest neighbours algorithm.

This study illustrates the possible bias when the prioritized requirements customization estimation (PRCE) algorithm available in the ERP literature is executed without any AI. Then, the authors present their newly developed AI version of the PRCE algorithm that uses ML techniques. The authors then discuss its adjoining algorithmic bias with an illustration. Further, the authors also draw a roadmap for managing algorithmic bias during ERP customization in practice.

To the best of the authors’ knowledge, no prior research has attempted to understand the algorithmic bias that occurs during the execution of the ERP customization algorithm (with or without AI).

This paper aims to investigate the impact of Industry 4.0 (I4.0) technologies on knowledge creation for innovation purposes by assessing the relationships among the variety of I4.0 technologies adopted (breadth I4.0), the penetration of these technologies within the firm’s value chain activities (depth I4.0) and the mediating role of both internal (inter-functional (IF)) and external [with knowledge-intensive business services (KIBS)] collaborations in this process.

The study employed a quantitative research design. By administering a survey to entrepreneurs, chief operation officers or managers in charge of the operational and technological processes of Italian manufacturing firms, the authors collected 137 useful questionnaires. To test this study's theoretical framework and hypotheses, the authors ran regression and mediation analyses.

First, the results highlight the positive link between breadth I4.0 and depth I4.0. Moreover, the results show the key role played by increased collaboration among the firm’s business functions and by relationships with KIBS in creating knowledge to innovate processes and products when I4.0 technologies are adopted.

The variety of I4.0 technologies adopted enables a firm to use such technologies in various value chain activities. However, the penetration of I4.0 into the firm’s value chain activities (depth I4.0) does not per se directly imply the production of new knowledge, for which a firm needs internal collaboration among different business functions, in particular with the production area, or collaboration with external partners that favor I4.0 implementation, such as KIBS.

To achieve innovation goals by creating new knowledge, especially in the manufacturing industries, firms should encourage internal and external collaboration when I4.0 technologies are adopted. Moreover, policy makers should not only consider fiscal incentives for the adoption of such technologies, but also encourage the building of networks between adopting firms and external actors.

The study is one of the first attempt that provides empirical evidence of how I4.0 enables the creation of knowledge to innovate processes and products, highlighting the relevance of collaboration both within the company and with external partners.

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.

Cloud Manufacturing (CM) is the manufacturing version of Cloud Computing and aims to increase flexibility in the provision of manufacturing services. On-demand manufacturing services can be requested by users to the cloud and this enables the concept of Manufacturing-as-a-Service (MaaS). Given the considerable number of prototypes and proofs of concept addressed in literature, this work seeks real CM platforms to study them from a business perspective, in order to discover what MaaS concretely means today and how these platforms are operating.

Since the number of real applications of this paradigm is very limited (if the authors exclude prototypes), the research approach is qualitative. The paper presents a multiple-case analysis of 6 different platforms operating in the manufacturing field today. It is based on empirical data and inductively researches differences among them (e.g. stakeholders, operational flows, capabilities offered and scalability level).

MaaS has come true in some contexts, and today it is following two different deployment models: open or closed to the provider side. The open architecture is inspired by a truly open platform which allows any company to be part of the pool of service providers, while the closed architecture is limited to a single service provider of the manufacturing services, as it happens in most cloud computing services.

The research shoots a picture of what MaaS offers today in term of capabilities, what are the deployment models and finally suggests a framework to assess different levels of development of MaaS platforms.

This study aims to focus on a key unanswered question about how digitalization and the knowledge processes it enables affect firms’ strategies in the international arena.

The authors conduct a systematic literature review of relevant theoretical and empirical studies covering over 20 years of research (from 2000 to 2023) and including 73 journal papers.

This review allows us to highlight a relationship between firms’ international strategies and the knowledge processes enabled by applying digital technologies. Specifically, the authors discuss the characteristics of patterns of knowledge flows and knowledge processes (their origin, the type of knowledge they carry on and their directionality) as determinants for the emergence of diverse international strategies embraced by single firms or by populations of firms within ecosystems, networks, global value chains or alliances.

Despite digital technologies constituting important antecedents and critical factors for the internationalization process, and international businesses in general, and operating cross borders implies the enactment of highly knowledge-intensive processes, current literature still fails to provide a holistic picture of how firms strategically use what they know and seek out what they do not know in the international environment, using the affordances of digital technologies.