Cipriano Forza

Purpose: Consumer goods firms often face severe shortages caused by forecast inaccuracy, where a few variants become unexpected bestsellers and trigger costly stockouts. This article positions the choice of lead-time reduction initiatives as a crucial decision for enhancing responsiveness and mitigating shortages and frames this decision as a performance-management prioritization problem under uncertainty. Design/methodology/approach: This work developed a pragmatic direction-selection framework grounded in a design science approach and applied in a case to guide managers in evaluating and prioritizing lead-time reduction initiatives. The framework integrates insights from the literature with feasibility-oriented evaluation criteria, applying the principles of multi-criteria decision analysis to assess initiatives in terms of expected return on investment (impact relative to effort) and implementation horizon. Findings: The study offers a theory-based, empirically validated framework for identifying and planning lead time reduction initiatives in a context of hard-to-predict demand, making explicit a performance-management logic for prioritizing responsiveness initiatives. The case shows that initiatives with attractive expected impact–effort profiles are not necessarily robust priorities once implementation risk and sensitivity to assumptions are considered. Research limitations/implications: The study advances performance-management research by reframing lead-time reduction as a decision problem under uncertainty and extending the focus from performance evaluation to intervention selection, translating dispersed responsiveness insights into a replicable prioritization logic, validated in a real case and supported by sensitivity checks. Practical implications: The study provides a stepwise decision-support tool that helps cross-functional teams prioritize feasible lead-time reduction initiatives and translate them into an implementation plan, with risk and sensitivity checks to avoid assumption-driven choices. Originality/value: The paper offers a validated innovative decision-support framework that operationalizes lead-time reduction as a performance-management choice under demand uncertainty, using an explicit prioritization logic to select responsiveness initiatives end-to-end.

Product variety in manufacturing has increased significantly, driven by technological advancements and growing demand for customisation. To meet diverse customer preferences, companies often overextend their portfolios without fully considering the resulting impact on manufacturing effectiveness. This study investigates how product variety is associated with quality conformance in continuous process manufacturing, an area underexplored in the existing literature, which predominantly focuses on discrete or assembly-based operations. Utilising production data from a large chemical manufacturer, logistic regression analysis was applied to examine how variety-related engineering parameters relate to the probability of non-conformance at the big-bag level. The analysis shows that ramp-ups, especially those associated with major changeovers, and short production uptimes are correlated with an increased likelihood of quality issues. Very infrequent production also appears to increase quality risks. Contrary to learning-curve expectations, products with medium and low production intensity showed lower odds of non-conformance than high-intensity products. These findings indicate the implications of product variety in continuous manufacturing environments. By identifying variety parameters that appear to contribute to quality risks, this study offers initial guidance for production planners and product portfolio managers aiming to balance product variety with quality conformance and overall manufacturing effectiveness.

Reconciling product flexibility with cost, delivery, and quality is an ambidextrous organizational capability known as mass customization capability. This study focuses on how this capability is affected by the joint implementation of three organizational practices––knowledge absorption from customers, product modularity, and online sales configurator use––that directly correspond to the three fundamental building blocks of mass customization identified by prior, influential research. By drawing upon a central tenet of resource orchestration theory, the fit-as-covariation perspective, and prior mass customization research, we conceptually develop the hypothesis that the fit-as-covariation of these practices has a stronger positive association with mass customization capability than the same practices implemented in isolation. This hypothesis was tested using covariance-based structural equation modeling and survey data from 213 manufacturing plants in three industries across 16 countries. Our results support the hypothesis, showing that the joint effect of these practices explains substantially more mass customization capability variation (41.9%) than their isolated effects (13.9%). This amount of variation indicates an effect size that is greater than that reported by most previous survey-based studies on the antecedents of this capability. Theoretically, this paper adds to the relatively limited body of knowledge on the relationships among the enablers of mass customization by highlighting the benefits of a holistic approach in the implementation of the three practices under investigation. Pragmatically, this study helps companies create flexible systems that are able to provide customized products without compromising cost, delivery, or quality.

This chapter is about surveys using questionnaires. It takes a processual view, moving from the theoretical model to hypothesis development to empirical investigation, and covers many general issues on sampling, validity, reliability and other issues common to all research approaches. Because of this, the chapter is important not only in itself, but also because of many fundamental issues valid across the subsequent chapters on specific approaches. It takes as a starting point conceptualization of the research issue through the development of a theoretical model and discusses the unit of analysis and definitions. The reader is then taken through the steps of detailed research planning, paying particular attention to the development of measures. Before going to present the survey execution activities, the chapter deepens advanced issues regarding the interdependences between the theoretical aspects (e.g. monadic/polyadic constructs) and survey design choices (e.g. single/multiple respondents). Special care is then given to how to analyse and interpret data, further discussing validity issues. Commonly used and advanced data-analysis methods are presented. Finally, emerging issues and techniques in data collection, management and analysis are presented such as data integration from multiple sources and data visualization. Along this chapter, the reader can see the evolution of operations and supply chain management survey research in the last 40 years.

Mass customization (MC), an organization’s ability to provide customized products and services that fulfil each customer’s idiosyncratic needs without considerable trade-offs in cost, delivery and quality, is gaining importance among companies. To help practitioners on the complex path towards MC, academic research has provided some guidelines for MC implementation. Recent reviews in this research sub-stream underlined the lack of MC implementation guidelines (MC-IGs) specifically developed for small and medium enterprises (SMEs) and also indicated the opportunity to use the design science research (DSR) strategy to develop new MC-IGs. The present research answers call for new MC-IGs by developing maturity grid-based MC implementation guidelines for SMEs that comply with the MC-IG building blocks and the MC-IG properties indicated by Suzić, Forza, et al. . The development of such guidelines followed a DSR strategy that included short- and long-term observational evaluations in two SMEs over three years.

Purpose: The operational capability of mass customization (MC) allows consumers to obtain products tailored to their idiosyncratic needs. This study aims to provide insights into the potential of this capability for countering a product's liability of foreignness – the negative effect of the out-group status of a product's country of origin (COO) on consumers' evaluations of the product.Design/methodology/approach: Based on the social identity approach, it is hypothesized that this liability is reduced when a consumer product is mass-customized rather than standardized as per a mass-production strategy. This hypothesis is tested using a mixed between- and within-subject experiment.Findings: When evaluating mass-produced sneakers, native German-speaking (Italian-speaking) South Tyrolean consumers rated the quality of Italian (German) sneakers significantly lower than that of German (Italian) sneakers. However, when the sneakers were mass-customized, this difference in perceived product quality was non-significant for both groups of consumers, supporting the research hypothesis.Research limitations/implications: Future research could replicate this study in other samples, with other product types, COOs and countries of destination, as well as at different degrees of product customization.Practical implications: Business-to-consumer firms contemplating the development of their MC capability are made aware that the benefits of this operational capability might go beyond the typical advantages highlighted by the existing literature.Originality/value: This paper joins the discussion on MC value by offering a theoretical explanation and empirical support for another mechanism through which the operational capability of MC can create value, at least in business-to-consumer industries: by countering a product's possible liability of foreignness and thus increasing perceived product quality in export markets.

Purpose: The development of mass-customization capability (MCC) is crucial for a growing number of manufacturing firms nowadays and presents great challenges, especially in the area of operations management. The purpose of this paper is to provide insights into which individual competencies (ICs) of an operations manager (OM) are important to the MCC of the manufacturing organization the OM works for.Design/methodology/approach: A multiple-case study was designed, involving eight machinery manufacturers in one European country, to collect data on their MCC and on the ICs of their OMs. Empirical case data were triangulated with analytical conceptual arguments grounded in the existing literature.Findings: The study provides empirical evidence of, and logical explanations for, the fact that OMs working in high-MCC manufacturing organizations use the ICs of negotiation, information seeking, efficiency orientation, analytical thinking and pattern recognition significantly more often than OMs employed by low-MCC organizations.Research limitations/implications: Future research could replicate this study in other industries and countries, as well as for other managerial roles.Practical implications: The study provides indications for OM selection and training in companies that are pursuing a mass-customization strategy.Originality/value: While the literature on technological and organization-level enablers of MCC has grown considerably, the understanding of its individual-level enablers is still limited and concerns mostly the workforce. This is the first study that relies not on practitioners’ opinions, but on data regarding manufacturers’ MCC and their managers’ ICs to shed light on which managerial competencies are important to a manufacturer’s MCC.