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This study aims to examine the role of hunger, environmental, economic, landfill and water shortage concerns as significant dimensions of consumer social awareness marketing in socially responsible plate food consumption.

To carry out their purpose, the authors validate the hypothesized model empirically through data from 1,536 households using structural equation modeling (SEM). In particular, the construct measures of the structural model have been tested by confirmatory factor analysis (CFA).

The outcome the authors came up with is coherent with the hypothesized model, and it proves a positive relationship of the five dimensions identified on consumer awareness. Moreover, the study results show the crucial role of landfill and water shortage concerns in measuring consumer awareness.

These findings may be of interest to practitioners, academics and policymakers for socially responsible food consumption guidance and training for planning consumer awareness programs. More in detail, this study offers the indication that the dimensions of the social consumer awareness construct are differing from commercial consumer awareness.

Even though several previous studies have addressed the concept of consumer awareness concerning product and service purchase decisions, this is one of the first research studies on consumer awareness as a multidimensional construct in social marketing studies domain.

This study aims to investigate the effects of open innovation (OI) and big data analytics (BDA) on reflective knowledge exchange (RKE) within the context of complex collaborative networks. Specifically, it considers the relationships between sourcing knowledge from an external environment, transferring knowledge to an external environment and adopting solutions that are useful to appropriate returns from innovation.

This study analyzes the connection between the number of patent applications and the amount of OI, as well as the association between the number of patent applications and the use of BDA. Data from firms in the 27 European Union countries were retrieved from the Eurostat database for the period 2014–2019 and were investigated using an ordinary least squares regression analysis.

Because of its twofold lens based on both knowledge management and OI, this study sheds light on OI collaboration modes and highlights the crucial role they could play in innovation. In particular, the results suggest that OI collaboration modes have a strong effect on innovation performance, stimulating the search for RKE.

This study furthers a deeper understanding of RKE, which is shown to be an important mechanism that incentivizes firms to increase their efforts in the innovation process. Further, RKE supports firms in taking full advantage of the innovative knowledge they generate within their inter-organizational network.

The study aims to investigate whether and how digital transformation, in terms of digital collaboration, joint efforts with internal/external partners to achieve common goals and the adoption of digital tools supporting this practice, affect social innovation capital in the context of small innovative enterprises (SIEs).

The research hypotheses derived from the analysis of the literature, evaluating how sharing resources, sharing intensity and digital patterns affect the collective capacity of SIEs to innovate, were investigated by applying multiple regression analysis. Data were retrieved from a sample of Italian SIEs through an online survey.

The main findings suggest that the propensity to spread resources and the sharing intensity positively affect the collective capacity of SIEs to innovate. Also, the effect of resources sharing on collective innovation increases as more digital patterns are used as tools. The connection is weaker for the intensity of resources sharing.

The study is conducted on Italian SIEs, a particular cluster of small and medium enterprises (SMEs). It would be interesting to compare and contrast the results of an analysis of a large sample of international companies, of different sizes and belonging to digital and non-digital sectors.

The results enrich the existing literature on social innovation capital, by clarifying its competitive benefits on the characteristic context of the SIEs and underlining the mediating role of the digital patterns.

This study aims to demonstrate the application of computer-aided text analysis (CATA) software in identifying primary associations and impressions of a specified tourist destination.

The Leximancer software is applied on primary information to analyze the concepts evoked by a destination. Because no specific planning has been done for destination image marketing strategies for rural tourism in Andalusia, this study visualizes and determines clusters of the main attributes associated with this destination.

The analysis identifies the main clusters among associations and impressions of the destination that can be useful in developing strategies.

Only a target segment is studied, with a relatively small sample size.

Leximancer can not only be applied to online user-generated content, but primary information can also be mapped to generate a holistic destination image. Furthermore, identification of the relevant attributes and impressions can serve to identify unique assets to help tourism organizations develop a destination.

Several implications concerning destination marketing are outlined.

Although previous studies have applied Leximancer and other CATA software, the present research uses a new approach. Deriving the primary information on destination image using an unstructured methodology, the concepts evoked by a destination are mapped. Because there is a lack of research on rural tourism in Andalusia and its destination image, its associated attributes are studied.

本论文展示如何使用CATA分析软件来确定一个具体旅游目的地的主要关系和印象。

Leximancer软件主要用于分析一个目的地引发的相关概念。因为安达卢西亚至今未有确定的乡村旅游目的地形象营销策略, 本论文视觉化和决定与此目的地相关的主要因素群。

研究结果指出了此安达卢西亚目的地的主要相关群和印象群, 这些对于指定战略计划有很大帮助。

本论文只研究了单一市场群, 分析样本量较小。

Leximancer不仅可以用来分析用户生成内容, 还可以分析主要信息, 以展示整体旅游目的地形象。此外, 分析指出的相关因素和印象群可以用来确立独特的资源组合, 帮助旅游机构开发旅游目的地。

本论文结构指出了多个旅游目的地营销的相关启示

尽管文献中有关Leximancer和其他CATA软件的使用文章, 本论文创立了新的使用方法。基于对旅游目的地形象的主要信息进行非结构性研究, 本论文对于旅游目的地的概念进行展开论述。由于至今未有针对安达卢西亚的乡村旅游研究以及旅游目的地形象研究, 本研究论述了其相关因素。

关键词 安达卢西亚、旅游目的地形象、旅游目的地因素、CATA软件、Leximancer

This paper aims to investigate the role of relational governance in innovation platform development, specifically investigating the context of living labs.

Two longitudinal case studies are presented, derived from auto-ethnographic narratives, qualitative interviews and secondary documents, which cover the critical stages in the development of each living lab.

Empirical insights demonstrate the relevance of coordination activities based on joint planning and activities to support innovation platform development across different stages. The governance role of research actors as platform activators is also identified.

The paper offers a useful perspective for identifying collective goals between living lab actors and aligning joint activities across different stages of living lab development.

The case provides insights into the challenges and opportunities for collaboration between academia, industry and users to support sustainable construction innovation.

A relational governance mode is identified, going beyond top down or bottom up approaches, which contributes a new understanding of how collective goals align within a relational space.

This paper aims to provide a comprehensive view of the different competition-based approaches that policymakers can exploit to foster external knowledge search and their positioning among innovation policy measures. A growing number of companies have implemented initiatives to access external knowledge to increase their innovativeness, consistently with the open innovation paradigm. Competition-based approaches have received increasing attention by the private sector as a way to access external knowledge. However, despite their potential role as innovation policy measures, a limited attention has been devoted so far to investigate them from the policymakers’ perspective.

To this aim, a two-stage empirical analysis has been carried out to develop a taxonomy of competition-based approaches. The first stage leveraged a multiple case study methodology including a sample of 20 competition-based approaches, while the second one leveraged interviews with Italian and European key informants.

This paper proposes a novel taxonomy including eight competition-based approaches, which differ among each other in terms of policy strategy, scope breadth and output required. Moreover, this paper enriches a well-established taxonomy of innovation policy instruments with the identified competition-based approaches.

This study contributes to the current debate on innovation policy by providing a taxonomy that includes eight competition-based approaches that can be exploited by policymakers to foster external knowledge search as well as their positioning among the innovation policy instruments. The taxonomy will hopefully support policymakers in identifying of the most suitable instruments in the light of their policy strategy and objectives.

This paper aims to present a dual-perspective framework for maintenance service delivery that should be used by manufacturing companies to structure and manage their maintenance service delivery process, using aggregated historical and real-time data to improve operational decision-making. The framework, built for continuous improvement, allows the exploitation of maintenance data to improve the knowledge of service processes and machines.

The Dual-perspective, data-based decision-making process for maintenance delivery (D3M) framework development and test followed a qualitative approach based on literature reviews and semi-structured interviews. The pool of companies interviewed was expanded from the development to the test stage to increase its applicability and present additional perspectives.

The interviews confirmed that manufacturing companies are interested in exploiting the data generated in the use phase to improve operational decision-making in maintenance service delivery. Feedback to improve the framework methods and tools was collected, as well as suggestions for the introduction of new ones according to the companies' necessities.

The paper presents a novel framework addressing the data-based decision-making process for maintenance service delivery. The D3M framework can be used by manufacturing companies to structure their maintenance service delivery process and improve their knowledge of machines and service processes.

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.

Design thinking has become an omnipresent process to foster innovativeness in various fields. Due to its popularity in both practice and theory, the number of publications has been growing rapidly. The authors aim to develop a research framework that reflects the current state of research and allows for the identification of research gaps.

The authors conduct a systematic literature review based on 164 scholarly articles on design thinking.

This study proposes a framework, which identifies individual and organizational context factors, the stages of a typical design thinking process with its underlying principles and tools, and the individual as well as organizational outcomes of a design thinking project.

Whereas previous reviews focused on particular aspects of design thinking, such as its characteristics, the organizational culture as a context factor or its role on new product development, the authors provide a holistic overview of the current state of research.