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The purpose of this paper is to analyze the relationship between knowledge management capabilities and successful open innovation within agri-food businesses. This particular piece of research focuses on agri-food businesses which utilize crowdfunding platforms.

The research adopts a survey-based methodology, which is useful in enhancing the generalization of results. The final sample includes 80 cases for the analysis. The model and the hypotheses were tested through a hierarchical regression model.

This research assesses the importance of knowledge management capabilities for successful open innovation in crowdfunding for agri-food businesses. In particular, it emerged that IT-based knowledge exploitation capabilities are enablers of open innovation strategies. Additionally, it emerged that knowledge exploration capabilities can positively mediate the relationship between IT-based knowledge exploitation capabilities and open innovation in the context of agri-food businesses.

To the authors’ best knowledge, few researchers have explored this topic and, as such, there is a need to better conceptualize this intriguing phenomenon and to provide empirical evidence to support it.

This article aims to provide a bibliometric and systematic literature analysis of studies published in the Journal of Intellectual Capital (JIC) from 2014 to 2018 in order to highlight emerging themes and future trends.

The analysis focused on 187 papers published on JIC over a period of five years. A scientometric approach to data mining enabled the detection of patterns in the dataset. Precisely, the investigation was conducted by integrating a bibliometric analysis on VOSviewer with a systematic literature review.

Four main streams of research on JIC emerged in the years of the analysis: reporting and disclosure of intellectual capital; intellectual capital research in universities, education and public sector; knowledge management; intellectual capital, financial performance, and market value.

The study offers valid insights to the topics covered by the Journal of Intellectual Capital by identifying the main research gaps and trends, along with future research avenues.

Prior scholars mostly focused on systematic literature reviews, whilst the use of bibliometric methods generally seems to be a missing tile in the research domain. Also, none of the extant studies has focused on the Journal of Intellectual Capital with reference to the 2014–2018 period. The use of both bibliometric and systematic approaches to literature review delivered extremely fine-tuned results in terms of factors such as citations, contents and evolution of clusters over time.

The purpose of this paper is to shed light on how big data deployment transforms organizational practices, thereby generating potential benefits, in a specific industry: retail.

To achieve the paper’s goal, the authors have conducted several semi-structured interviews with marketing managers of four retailers in Italy, and researched secondary data to get a broader picture of big data deployment in the organizations.

Data analysis helped identify specific aspects related to big data deployment, data gathering methods, required competences and data sharing approaches.

Despite the growing interest in big data in various fields of research, there are still few empirical studies on big data deployment in organizations in the management field, and even fewer on specific sectors. This research provides evidence of specific areas of analysis concerning big data in the retail industry.

Designing knowledge management (KM) systems capable of transforming big data into information characterised by strategic value is a major challenge faced nowadays by firms in almost all industries. However, in the managerial field, big data is now mainly used to support operational activities while its strategic potential is still largely unexploited. Based on these considerations, this study proposes an overview of the literature regarding the relationship between big data and business strategy.

A bibliographic coupling method is applied over a dataset of 128 peer-reviewed articles, published from 2013 (first year when articles regarding the big data-business strategy relationship were published) to 2019. Thereafter, a systematic literature review is presented on 116 papers, which were found to be interconnected based on the VOSviewer algorithm.

This study discovers the existence of four thematic clusters. Three of the clusters relate to the following topics: big data and supply chain strategy; big data, personalisation and co-creation strategies and big data, strategic planning and strategic value creation. The fourth cluster concerns the relationship between big data and KM and represents a ‘bridge’ between the other three clusters.

Based on the bibliometric analysis and the systematic literature review, this study identifies relevant understudied topics and research gaps, which are suggested as future research directions.

This is the first study to systematise and discuss the literature concerning the relationship between big data and firm strategy.

Effectively handling knowledge is crucial for any organization to survive and prosper in the turbulent environments of the modern era. Leadership is a central element for knowledge creation, acquisition, utilization and integration processes. Based on these considerations, this study aims to offer an overview of the evolution of the literature regarding the knowledge management-leadership relationship published over the past 20 years.

A bibliometric analysis coupled with a systematic literature review were performed over a data set of 488 peer-reviewed articles published from 1990 to 2018.

The authors discovered the existence of four well-polarized clusters with the following thematic focusses: human and relational aspects, systematic and performance aspects, contextual and contingent aspects and cultural and learning aspects. The authors then investigated each thematic cluster by reviewing the most relevant contributions within them.

Based on the bibliometric analysis and the systematic literature review, the authors developed an interpretative framework aimed at uncovering several promising and little explored research areas, thus suggesting an agenda for future knowledge management-leadership research. Some steps of the paper selection process may have been biased by the interpretation of the researcher. The authors addressed this concern by performing a multiple human subject reading process whose reliability was confirmed by a Krippendorf’s alpha coefficient value >0.80.

To the best knowledge, this is the first study to map, systematize and discuss the literature concerned to the topic of the knowledge management-leadership relationship.

The study aims to explore the interplay between open innovation and intellectual property. Differently from previous studies, we argue that open innovation fosters firm's patenting activity.

We use linear regression analysis to test model's hypotheses. Data are drawn from the Eurostat statistics and refer to a large sample of European firms (NACE Rev.2).

The findings confirm that open innovation fosters patenting activity in health care, also thanks to huge governments' expenditures in this market.

The study focuses solely on European firms and it adopts a traditional linear approach. So, we cannot exclude that different dynamics may occur across European borders. Future research should address this concern by focusing on multi-country comparative studies.

Open innovation is the most suitable model for health industry, because it improves both innovation performance and intellectual capital of firms.

The study tackles an existing gap of the literature by considering how the presence of large customers impacts the strength of intellectual property protection.

This paper aims to investigate the effect of auditor switching and lowballing on conditional conservatism, particularly how different types of auditor switching, namely, upward, downward and lateral switching to/from Big 4 and industry specialists, affect earnings quality in the following selected Asian countries: Indonesia, Malaysia, the Philippines, South Korea and Thailand.

Using conditional conservatism as a proxy for earnings quality, this study hypothesises that upward switching from non-Big 4 to Big 4 auditors, or from non-specialist to specialist auditors, would result in high conditional conservatism, while downward switching would lead to low conditional conservatism. The study further tests whether lowballing provides a viable explanation for reduced earnings conservatism in firms that switch from Big 4 to non-Big 4 auditors, or from specialist to non-specialist auditors.

The analysis, on a sample of 28,073 firm-year observations from 2007 to 2016, shows that the decision to downgrade auditors leads to lower conditional conservatism in the year of switching, compared with other firms and the pre-switching year. The evidence further shows that, when firms downgrade their auditors, lowballing contributes to a decrease in conditional conservatism in the first year of audit switching. Further, this research finds that switching to specialist auditors will result in increased conditional conservatism, while switching from specialist auditors to non-specialist auditors will result in reduced conditional conservatism.

The findings of this study are useful to investors who are looking to diversify their investment portfolio in developing markets, as evidence about auditor switching and quality of financial reporting may be an important factor in their investment decisions. Downward auditor switches and lowballing could act as red flags to investors in the sense that these events could signal a decrease in conditional conservatism and, hence, quality of earnings.

This research offers new evidence to support the view that management decisions to switch to lower-quality auditors will force newly appointed auditors to acquiesce to clients’ demands for reporting low-quality earnings.

The Saint Valentine's Decree (1984) and the ensuing hard‐fought referendum (1985), which reduced the automatisms of scala mobile, started a process of redefinition of wage fixing in Italy, which culminated with the final abolition of scala mobile (1992) and the approval of Protocollo d'intesa (1993). Since then, following new corporatist principles, a national system of centralised wage bargaining (concertazione) and so‐called “institutional indexation” have governed the determination of wages. Does incomes policy generate greater coordination in the process of wage formation? Does it cause greater co‐movement of wages, prices, labour productivity and unemployment? This paper aims to answer these questions with reference to one of the G8 economies.

After testing for unit root each component by using the ADF, Phillips and Perron, DF‐GLS and Zivot and Andrews statistics, the paper tests for co‐integration the so‐called WPYE model using different methods. The Engle and Granger approach is used to assess the impact of incomes policy on the speed of adjustment of real wages, productivity (and unemployment) to their equilibrium value, while the Gregory and Hansen procedure serves as a means to endogenously detect the presence of a regime shift. The paper estimates coefficients before and after the structural break.

Incomes policy based on the 1993 Protocol has caused a regime shift in the process of wage determination. The long‐run estimates of the WPYE model do not generate stationary residuals except when a dummy for 1993 is added. The share of wages over GDP reduces by about ten percentage points in the early 1990s and has stood at about 57 per cent since 1995. The link with productivity is close to one‐to‐one only before the break. The feedback mechanism, as measured by the coefficient of lagged residuals in short‐run estimates, is increased from −0.46 in the pre‐reform to −0.79 in the post‐reform period, suggesting that incomes policy has increased real wage flexibility indeed. In recent years the link between real wages and (very low) labour productivity growth has weakened. In a sense, incomes policy has introduced a new form of (upward) wage rigidity. Last but not least, incomes policy has changed the correlation with the unemployment rate from positive to not statistically significant.

Future developments will focus on disentangling the impact of incomes policy vis‐à‐vis other policy interventions on WPYE and on unemployment.

The analysis calls for a careful revision of the 1993 Protocol aimed at better protecting the purchasing power of real wages without losing control on inflation, and introducing growth‐generating mechanisms.

The paper studies the impact of incomes policy on WPYE and the Phillips curve by means of co‐integration and structural break analysis. It proposes to interpret the effect of incomes policy on the Phillips curve as changing the coefficient of the error correction mechanism that leads real wages to their long‐run equilibrium value.

This paper aims to estimate the delay or timely effects of the national vaccination strategy for COVID-19 on Italian gross domestic product (GDP). By adopting a knowledge management lens, the study highlights the importance of “time” for Italian recovery. Indeed, recovering an adequate growth rate is crucial for the future of employment, well-being and management of Italian public debt.

This study applies an epidemiological model of a universal access vaccination programme against COVID-19. The economic model is based on the time-shift of available quarterly projections deriving from the expected delay or acceleration of the national vaccination plan against COVID-19.

The basic concept underlying the scenario analysis is that the sustainability of the expected recovery of the Italian economy due to the COVID-19 shock, and consequently the growth of the GDP, is time-dependent on the rollout of the national vaccination plan.

A delay in the vaccination campaign could have a twofold negative impact on the growth of the Italian gross product: it reduces the quarterly growth over the previous year in the short term and it delays the quarterly upwards trend over the next two years. Policymakers and practitioners are called to promptly face new dynamic scenarios due to public and economic policies to fight the COVID-19 crisis.

To the best of the authors’ knowledge, this is the first attempt of research that focuses attention on the synchrony between the economic time necessary for recovery and the real-time necessary to achieve vaccination coverage for the restart of production activities.

Recognising the increasing relevance of digital platforms in socio-economic dynamics, the paper aims at investigating in which ways digital platforms can influence the economic performances of Italian small and medium enterprises (SMEs) actively engaged in foreign countries.

The paper adopts the interpretative lens provided by the exploration–exploitation dichotomy within current studies in knowledge management for defining knowledge-based factors able to influence the economic performance of Italian SMEs in foreign countries. An explorative study on secondary data related to 746 Italian SMEs is conducted for testing via structural equation modelling (SEM) the positive relationships between (1) SME's investment in information and communication technologies (ICT), (2) number of languages available for the SME's website and (3) number of languages available for SME's social pages and SME's return on sales (ROS) in foreign countries.

The results underline the key role of exploitation factors in terms of influence on SME's performance in foreign countries.

The paper enriches current studies about international marketing providing preliminary evidence about the key role of exploitation factors in influencing SME's performance in foreign countries.