Italian Manufacturing Research Articles

The Workplace Health Promotion project in an Italian manufacturing

Abstract Introduction The Workplace Health Promotion (WHP) program aims to improve employee’s health and well-being in the workplace by intervening in lifestyles. The objective of our study was to assess the impact of the WHP promoted by the Local Health Authority Tuscany South-East at a manufacturing. Methods The program was set at the STOSA Company in Radicofani (Siena, Italy) between 31 May 2017 to 31 December 2021, with a one-year interruption due to the COVID-19 pandemic. Based on an assessment of the workers’ health status, we identified nutrition and fighting smoking as areas of intervention. The WHP project was integrated into the company policy and targeted all staff. Evaluation of interventions was conducted using an anonymous paper questionnaire (Regional Decree no. 1565, Annex 3) administered in three moments: at the beginning of the project (T0), one year later (T1), and at the end (T2). We conducted a descriptive and inferential analysis (chi-square test) with R. Results We collected 131 (T0), 136 (T1), and 123 (T2) responses. The cohort is composed entirely of males (T0 M:F 122:8, T1 130:6, T2 109:14). The median age is 40 years (SD 8.24 (T2)). There is a statistically significant difference in the perception of health status by education (p<.001), type of work (p<.001), smoking habit (p<.001), and the change in smoking habit (p<.001). The whole sample positively evaluated the interventions on nutrition and fighting to smoke. Moreover, the entire sample reported improvements in their diet since the beginning of the project. Conclusions The COVID-19 pandemic caused difficulties in carrying out the project and possible changes in workers’ lifestyles. However, positive outcomes were observed in the targeted areas. The company has evaluated positively the WHP’s project and decided to maintain the good practices acquired. Key messages • The workplace represents a privileged setting to promote healthy lifestyles and prevent non-communicable diseases. • Collaborations between health authorities and other sectors are strategic to reach the general population.

Firm interconnectedness and resilience: evidence from the Italian manufacturing

Abstract This article explores how firm interconnectedness determines firm-level resilience. We argue that firms that engage in outward foreign direct investment are more interconnected, and therefore better equipped to deal with structural and economic shocks, than firms that are not engaged in outward foreign investment. Interconnectedness is measured along two dimensions; cross-border firm linkages and embeddedness in interconnected regions. We use a sample of 13,000 Italian manufacturing firms during the period 2008–2011. We find a positive association between firm interconnectedness and resilience. Moreover, we find the firms that operate in more interconnected regions to be more resilient than firms that operate in relatively isolated regions. Our results offer new insights into the complex interaction between firm and regional interconnectedness.

Fostering digital trust in manufacturing companies: Exploring the impact of industry 4.0 technologies

This study examines the multifaceted impacts of digital innovations on organisational structures and stakeholders ‘commitment. The integration of digital technologies, including information technologies, IoT, AI, AR/VR, blockchain, robotics, and automation, underscores the indispensable role of trust in contemporary business operations. Focusing on Italian manufacturing firms at the forefront of Industry 4.0 implementation, this research seeks to unravel the nuanced factors contributing to digital trust. A comprehensive framework, derived from an integrative literature review, categorises two distinct groups of factors influencing a firm's decision to establish digital trust. Employing a configurational approach, specifically Qualitative Comparative Analysis (QCA), the joint impacts of multiple factors on digital trust levels are scrutinized, offering insights into how different elements synergise to trigger digital trust. This study aims to bridge existing gaps in understanding the intricate dynamics of trust within organisations undergoing digital transformation.

Compare and Contrast of Knowledge Sharing in Virtual Teams in IT Companies and Manufacturing Industries using the Theory of Planned Behavior

The purpose of this research work is to Compare and Contrast of Knowledge Sharing in Virtual teams in IT companies and Manufacturing industries Using the Theory of Planned Behaviour. In this research study, we understand the Theory of Planned Behaviour (TPB) Models with Structural Equation Modeling Methodology. In this research study, we use TOOLS like IBM SPSS (Statistical Package for Social Sciences), IBM AMOS, TABLEAU. Scope of Virtual Teams Though virtual teams hope deeply on information and communication technology but it is not just circumscribed to the IT industry. Today almost every industry sector extending from construction, academics, manufacturing, non-profit, automotive and healthcare and to retail are promoting virtual teams. From corner to corner of the world, on one hand loftier organizations like Hewlett Packard, Whirlpool, Texas Instruments, British Petroleum etc with their gigantic possessions and proficiencies fascinated on the doles of virtual teams to strengthen their efficiency and services to customer. Fundamentally all principal occupations or job roles like Research and development, engineering, finance, sales, logistics, business development and Human resources can be consummated in a virtual atmosphere. As Covid 19 affected the globe and made a huge loss, virtual teams supported the tantrum hence letting the company employees not to fail in performing their job roles.

Analysis and Modelling for Industrial Energy Efficiency in the Cosmetics Industry: A Real Industrial Case in an Italian Manufacturing Company

Economic and environmental issues translating into energy costs and pollution within the production environment are increasingly attracting attention. Industrial Energy Efficiency (IEE) is gaining ever-higher importance within production environments. Since cosmetic consumers and companies are becoming increasingly sensitive to sustainability, the cosmetic field is working to reduce the environmental and social impact along the whole supply chain. Furthermore, IEE actions in business processes can lead to several medium- and long-term economic and environmental benefits. This paper is the first work in the literature presenting a real-case application of energy analysis and modeling to achieve better energy performances in a cosmetics production process. Thus, in the body of knowledge, it contributes by providing a real case of good practice to be benchmarked for future IEE interventions in cosmetics manufacturing processes. The work has been conducted by analyzing the production process’s energy consumption and developing an energy model of a selected machine (i.e., a turbo-emulsifier). The analysis and modeling performed aimed at assessing the different operational phases of the machine and evaluating the different behaviors of the data. Finally, the results allowed us to propose possible improvements to be applied to the production process to achieve better energy performances.

Probability of Corporate Bankruptcy over Two Periods of Crisis (2007-2010 vs 2019-2022): Application to Italian Manufacturing SMEs Using a Three Years Rating Model

Probability of Corporate Bankruptcy over Two Periods of Crisis (2007-2010 vs 2019-2022): Application to Italian Manufacturing SMEs Using a Three Years Rating Model

Private welfare for workers. Corporate welfare at Fiat in the era of Vittorio Valletta (1946-1966)1

ABSTRACT Fiat (Fabbrica Italiana Automobili Torino) was for a good part of the twentieth century Italy’s largest industrial company. Historians and sociologists have extensively investigated its productive expansion in the automotive industry, as well as the leading role it played in introducing and applying Taylorist and Fordist techniques of mass production to the Italian manufacturing sector. The analysis of the organization of the social policies that the company established for its employees from the 1920s onward has been, however, less considered. Yet, the complex of welfare, recreational and cultural services made available to workers was so pervasive that it seems interesting to reconstruct its history and assess the impact it had on the lives of employees. It can be argued that the corporate welfare made up by the Turin company during the years when Vittorio Valletta led it (1946–1966) was an integral element of the Fordist model of mass production, aimed not only to counterbalance the strain of assembly line work with social benefits, but also to replicate in daily life the regimentation that office and factory workers experienced in the hours they spent in the mills.

Does family power drive the size transition of entrepreneurial family firms? A study on the growth of Italian manufacturing firms

PurposeThis paper explores the drivers and inhibitors of the transition of entrepreneurial family firms from small to large firms. We adopt two contrasting theoretical perspectives, i.e. agency and stewardship, to explore the effects of family power on size transition.Design/methodology/approachWe adopted an original research design that leverages a unique longitudinal database built starting from the list of the 500 best Italian manufacturing family firms published by the AUB Monitor in 2018. Specifically, we tested our hypotheses using a comprehensive set of financial and governance data from 89 Italian manufacturing family firms covering a 10-year period. To test our hypotheses, we conducted a survival analysis using a Cox regression.FindingsWe find an inverted U-shaped relationship between family involvement in ownership and size transition: size transition is more likely to happen at intermediate levels of family involvement in ownership. Additionally, our analysis shows that family involvement in the board of directors negatively impacts size transition, while the presence of a family CEO has a positive influence.Originality/valueTo the best of our knowledge, this study represents the first exploration of the phenomenon of size transition within entrepreneurial family firms. We believe it was worthwhile for two reasons. First, small size is frequently regarded as a weakness when competing in international markets, investing in R&D, or rewarding shareholders. Second, since small family firms are the major contributors to the world economy, understanding the factors that facilitate their transition to large firms can have a significant impact on overall economic development and prosperity.

Financial constraints prediction to lead socio-economic development: An application of neural networks to the Italian market

This study applies a neural network framework to optimize the classification of firms and to predict their difficulties in collecting external financial resources in the short term. In detail, we adopt replicated bootstrapped algorithms optimized on sensitivity and specificity as error measures and we propose a comparative analysis to identify the best-performing one. According to our results, the Conjugate gradient backpropagation with Fletcher-Reeves updates (i.e., CGF) is the best-performing algorithm, with sensitivity equal to 74.41 % and specificity equal to 70.11 %. Then, we use this algorithm and its weights to provide a classification of the Italian manufacturing industry in 2019, identifying the geographical areas in which firms under financial constraints are located, as well as the most critical industrial sectors. Based on this evidence, and considering the implementation of a cohesion policy, we highlight interventions by policy makers to support firms’ access to the capital market, fostering their investments and the consequent socio-economic development.

Internationalization and financial constraints: Opportunities, obstacles, and strategies

This study delves into the relationship between financial constraints and internationalization, investigating the role and extent of variability in access to the capital market in shaping internationalization strategic choices. In detail, focusing on the Italian manufacturing industry between 2013 and 2019, we examine this relation disentangling the effect between export and import dynamics. Initially, we run various OLS regression models to investigate the profile of exporting/importing firms, providing a preliminary picture of the internationalization process of the Italian manufacturing industry. Then, we run several GMM regression models to highlight these dynamics over time and to collect robust evidence for our hypotheses. According to the results, we observe that firms under high financial constraints have the lowest intensity of import and export flows (i), firms under moderate financial constraints have the highest intensity of export flows (ii), and firms under low financial constraints have the highest intensity of import flows (iii). An interpretation of these results concerns the heterogeneity of business-to-business payment dynamics across the EU global value chain, with the Italian market characterized by the longest delay. Hence, internationalization through export flows represents an opportunity for those companies with the most aggressive business strategies, quickly raising their internal liquidity, and complementing local financial debts with international trade credits. On the other hand, only firms with no restrictions to the capital market can afford prompt payments of foreign suppliers, easily collecting the necessary liquidity to support import flows.

Pandemic crisis and firm survival: evidence from the Italian manufacturing industry

Pandemic crisis and firm survival: evidence from the Italian manufacturing industry

Are lean and digital engaging better problem solvers? An empirical study on Italian manufacturing firms

PurposeWe studied the relationship between job engagement and systematic problem solving (SPS) among shop-floor employees and how lean production (LP) and Internet of Things (IoT) systems moderate this relationship.Design/methodology/approachWe collected data from a sample of 440 shop floor workers in 101 manufacturing work units across 33 plants. Because our data is nested, we employed a series of multilevel regression models to test the hypotheses. The application of IoT systems within work units was evaluated by our research team through direct observations from on-site visits.FindingsOur findings indicate a positive association between job engagement and SPS. Additionally, we found that the adoption of lean bundles positively moderates this relationship, while, surprisingly, the adoption of IoT systems negatively moderates this relationship. Interestingly, we found that, when the adoption of IoT systems is complemented by a lean management system, workers tend to experience a higher effect on the SPS of their engagement.Research limitations/implicationsOne limitation of this research is the reliance on the self-reported data collected from both workers (job engagement, SPS and control variables) and supervisors (lean bundles). Furthermore, our study was conducted in a specific country, Italy, which might have limitations on the generalizability of the results since cross-cultural differences in job engagement and SPS have been documented.Practical implicationsOur findings highlight that employees’ strong engagement in SPS behaviors is shaped by the managerial and technological systems implemented on the shop floor. Specifically, we point out that implementing IoT systems without the appropriate managerial practices can pose challenges to fostering employee engagement and SPS.Originality/valueThis paper provides new insights on how lean and new technologies contribute to the development of learning-to-learn capabilities at the individual level by empirically analyzing the moderating effects of IoT systems and LP on the relationship between job engagement and SPS.

Data Science Supporting Lean Production: Evidence from Manufacturing Companies

Research in lean production has recently focused on linking lean production to Industry 4.0 by discussing the positive relationship between them. In the context of Industry 4.0, data science plays a fundamental role, and operations management research is dedicating particular attention to this field. However, the literature on the empirical implementation of data science to lean production is still under-investigated and details are lacking in most of the reported contributions. In this study, multiple case studies were conducted involving the Italian manufacturing sector to collect evidence of the application of data science to support lean production and to understand it. The results provide empirical proof of the link and examples of a variety of data science techniques and tools that can be combined to support lean production practices. The findings offer insights into the applications of the traditional lean plan–do–check–act cycle, supporting feedback on performance metrics, total productive maintenance, total quality management, statistical process control, root cause analysis for problem-solving, visual management, and Kaizen.

Multiple banking relationships: the role of firm connectedness

Abstract This paper sheds light on the role of firm social connectedness in multiple banking relationships, controlling for other firm-level determinants. Using a large sample of Italian manufacturing firms, we develop novel text-based measures of firm connectedness and multiple banking relationships. We measure firm connectedness by exploiting information on the number of links that a non-financial firm has with any other non-financial firm through individuals who hold a position (such as shareholder, administrator, and technical or administrative employee) in both firms. The paper finds empirical evidence that firm connectedness is positively associated with the number of banks lending to the firm. This effect is stronger for younger, smaller, and more indebted firms, suggesting that firm connectedness favors the diffusion of soft information and ultimately their access to multiple sources of credit by reducing negotiation and transaction costs. Connectedness, on the other hand, does not seem to reduce firms’ incentives to increase the number of lenders in order to minimize hold-up risks.

Leverage and SMEs financial stability: the role of banking competition

This work exploits a large panel dataset on Italian manufacturing SMEs to examine the relationship between leverage and firms’ financial stability. Specifically, we evaluate whether and to what extent this link is affected by the degree of competition characterising the local credit market in which firms operate. Using two measures of local banking competition – the H-statistic and the Boone indicator – our evidence indicates that the negative impact of leverage on firms’ financial health is greater for firms operating in more competitive banking markets. A plausible interpretation of this finding is that the competition drawbacks could prevail on its expected advantages, leading banks to be less inclined to establish lending relationships with risky firms, thus exacerbating their financial vulnerability.

Counterfeiting and firm survival. Evidence from the Italian manufacturing industry

Using a dataset obtained by matching and merging three major databases, this paper investigates the impact of counterfeiting on firm survival in a sample of Italian manufacturing firms established between 2004–2006. This paper contributes to the literature on firm survival, which has identified firm-level characteristics, macroeconomic conditions and institutional features as key contributing factors to growth and survival probability among firms. The topic is hugely significant since this illegal competition may displace and damage the firms that produce genuine products. Overall, our analysis finds that the presence of counterfeit products negatively affects the chances of firms surviving. Moreover, after performing an in-depth analysis, we find that the presence of counterfeit products affects firms operating in lower tech sectors and smaller in size. Our evidence, which is robust to an alternative measure of counterfeiting and different estimation methods, provides room for policy interventions.

Manufacturing Analytics System: A New IT Category Enabling Next-Level Operational Excellence

The manufacturing sector is undergoing a substantial digital transformation. Following decades of developments in data capture technologies, computer science, and IT infrastructure, manufacturers collect and store more data than ever. However, collecting data is one challenge; another is using it. Many manufacturers are struggling to take advantage of the possibilities offered by advanced analytics. This paper introduces a new category of industrial IT system that solves this problem: the Manufacturing Analytics System (MAS).

Generating modern heritage through changing urban environments and identities: A case study from Prato's (Italy) industrial district, history, and multiculturalism in a polycentric urban setting

AbstractFollowing economic crises, the evolution of industrial districts (IDs) has frequently caused the crisis within entire urban systems. Being IDs based on individual will and competences, rather than on big industries, their failure can compromise the city's identity. The Italian manufacturing industry consistently relied on this process, and this paper analyzes the case study of Prato, a medieval core city in central Italy that, since the mid‐twentieth century, developed a world‐class textile district based on a polycentric production structure and widespread family entrepreneurialism. During the global economic crisis of the early 2000s, production almost stalled, leaving the city without the core of a collective identity, but with a legacy of empty spaces. Significant foreign migration, in particular from China, filled these spaces, consolidating the clothing sector. The study investigated the city's contemporary identities resulting from the rapid change in people, activities, and spaces.

Artificial Intelligence: The Future

Artificial intelligence is the intelligence of machines or software, as opposed to the intelligence of humans or animals. It is also the field of study in computer science that develops and studies intelligent machines. "AI" may also refer to the machines themselves. AI is not a new for the scientist, it was introduce in 1943 with artificial neurons model and get popular in 1950 due to “Turting test” the test was done to get answer that machine can think?, purposed by Alan Turing. Basically AI is categorized into three types, Artificial Narrow Intelligence, Artificial General Intelligence and Artificial Super Intelligence. Deep learning and machine learning is major subfield of Artificial intelligence. DL as a subset of ML, which is also another subset of AI. Therefore, AI is the all-encompassing concept that initially erupted. Application of AI fields are Healthcare, Business, Education, Agriculture, Finance, Law, Entertainment and media, Software coding and IT processes, Security, Manufacturing, Banking and Transportation. In reference to Job creation or distraction, Artificial Intelligence is not job killer but a job category killer”. In the latest report (May 2023) on The Future of Jobs, the World Economic Forum (WEF) predicts the creation of 69 million jobs by 2027 thanks to AI, but also the destruction of 89 million jobs. In context to intelligence level, Jan. 2022, Age of IQ level of AI was as 7 year Children and in Dec. 2022, Age of IQ level of AI was as 9 year Children. India is emerging market in global and it has around 12 % of work could be automated by AI. In India more than 2000 startup are related to AI and 90000 plus AI Professional work in India.The economic impact of AI, for select G20 countries and estimates AI to boost India’s annual growth rate by 1.3 percentage points by 2035. AI has potential to add 1 trillion to India’s economy in 2035. We are going to enter into new technological world, it’s may be our fortune or misfortune. Key Words: - Artificial Intelligence, Machine learning, Job, India

Actors, resources, and activities in Digital Servitization: a business network perspective

Digital Servitization (DS), that is the development of new services through the use of digital technologies, is an emerging research stream characterized by an inherent complexity that requires understanding changes occurring over time and impacting relationships and network dynamics. Scholars have argued for the need to move towards an analysis of the micro-interaction processes and the adoption of a networking perspective. In this direction, this study aims to explore the contribution of the business network approach, compared to other existing frameworks, in the analysis of complex digital phenomena. To reach this aim, the study undertakes a single case study of an Italian manufacturer which is undertaking a DS process. The empirical analysis is guided by the three dimensions of the interpretative Actors-Resources-Activities (ARA) framework, developed within the Industrial Marketing and Purchasing (IMP) approach. The analysis has provided insights into each of the three layers of the ARA framework and has pointed to a continuous interrelation between the internal and external context and interdependence among the three layers. The study provides a theoretical contribution to the stream of literature dealing with the DS phenomenon by providing a unified theoretical approach - i.e., the business network approach - characterized by analytical completeness. Also, the research paves the way for the business network approach and for the ARA framework to be adopted in the investigation of complex business phenomena, such as DS.