Search results

The purpose of this paper is to investigate three issues: how does an innovative search (local search and boundary-spanning search) impact firm innovation performance of latecomers; how does capability reconfiguration (capability evolution and capability substitution) mediates the relationship between innovative search and firm innovation performance; and how does the technological leapfrogging process (initial stage, following stage, synchronization stage and leading stage) moderate the relationship between capability reconfiguration and firm innovation performance.

A “resource-capability-performance” theoretical framework was developed to explore the relationships between local/boundary-spanning search, capability reconfiguration and firm innovation performance. The data were collected by sending out surveys to managers and employees in various industries in mainland China. These hypotheses were tested using structural equation models and hierarchical regressions.

The results showed that: innovative search has a direct causal relationship to capability reconfiguration; local search and boundary-spanning search are conducive to improve the innovation performance of latecomers; the impact of local search and boundary-spanning search on innovation performance is realized through the completion of mediating role of capability reconfiguration; there are differences in the path of local search and boundary-spanning search affecting the capability reconfiguration of enterprise innovation performance; and the relationship between innovative search, capability reconfiguration and enterprise innovation performance evolves with the enterprise in different stages of technological leapfrogging.

This study explores the relationship and the path of innovative search to firm innovation performance and analyzes the path difference between local search and boundary-spinning search, which enriches the research of organizational search and enterprise innovation. This paper reveals the whole path of innovative search affecting innovation performance, discusses the important role of capability reconfiguration and makes incremental contributions to dynamic capability theory. It studies the evolution of innovative search on innovation performance under the background of technological leapfrogging, which provides a new perspective for the study of organizational search and capability-based theory.

The purpose of this study is to identify major themes and potential research opportunities in online and offline consumer search.

A systematic review was conducted based on 118 articles identified from prevalent journal databases. Keywords frequency analysis was carried out to identify the major themes. An inductive thematic analysis was carried out to verify the generated themes.

Results show that uncertainty, knowledge, perceived risk, price, experience and involvement are the major themes associated with consumer information search. Uncertainty, one of the major themes of offline search, has not been studied in the online search context. Similarly, the previous experience needs to be explored in the context of the offline search. Finally, potential research opportunities for future research has been summarized based on the retrieved themes.

The systematic review provides an in-depth understanding on the current research on information search literature with future research directions.

This study helps retailers to understand the key elements that motivate consumers to perform external information searches from online and offline sources and to curate targeted information provision strategies to influence purchase decisions.

Consumers with limited internet availability may access channels prior to decision-making. The themes identified in this study can aid policymakers to design affordable access to these channels.

This study adds to the sparse literature on systematic reviews on consumer search for online and offline channels.

Semantic retrieval and discovery of datasets published as open data remains a challenging task. The datasets inherently originate in the globally distributed web jungle, lacking the luxury of centralized database administration, database schemes, shared attributes, vocabulary, structure and semantics. The existing dataset catalogs provide basic search functionality relying on keyword search in brief, incomplete or misleading textual metadata attached to the datasets. The search results are thus often insufficient. However, there exist many ways of improving the dataset discovery by employing content-based retrieval, machine learning tools, third-party (external) knowledge bases, countless feature extraction methods and description models and so forth.

In this paper, the authors propose a modular framework for rapid experimentation with methods for similarity-based dataset discovery. The framework consists of an extensible catalog of components prepared to form custom pipelines for dataset representation and discovery.

The study proposes several proof-of-concept pipelines including experimental evaluation, which showcase the usage of the framework.

To the best of authors’ knowledge, there is no similar formal framework for experimentation with various similarity methods in the context of dataset discovery. The framework has the ambition to establish a platform for reproducible and comparable research in the area of dataset discovery. The prototype implementation of the framework is available on GitHub.

This paper aims to test the influence of external information search (EIS) on knowledge elaboration and group cognitive complexity (GCC) under the moderating effect of absorptive capacity (AC is indicated by prior knowledge base and gender diversity).

The results of three studies (one field study and two experimental studies) are reported. The first study tests the interaction between EIS and the two dimensions of AC on group knowledge elaboration in a sample of 65 organizational groups. In the second study, EIS was directly manipulated and the interaction with AC in a sample of 65 groups was tested. In the last experimental study, the AC of the boundary spanner (highest level of expertise versus lowest level of expertise) was manipulated and the effects of EIS in a sample of 37 groups were tested.

The first study reveals a significant interaction between EIS and prior knowledge base on knowledge elaboration and points toward a compensatory interplay of EIS and AC on GCC. The results of the second study indicate that EIS increases the time spent on task, as well as the efficiency of knowledge integration (GCC per unit of time). Furthermore, EIS has the strongest positive effect on GCC in groups in which at least one of the AC dimensions is average or high. The results of the last study show that the AC of the boundary spanner compensates for the lack of absorptive capacity of the group and also show that the cognitive distance between the boundary spanner and the rest of the group has a negative influence on the efficiency of knowledge integration in groups.

The limitations of Study 1, common to non-experimental research (related to causality), are dealt with in the second and third studies that establish causality between EIS and GCC.

The paper has important implications for the management of information search effort in organizational groups, in particular the groups are advised to: engage in EIS to increase their cognitive repertoire and cognitive complexity, delegate, when possible, their most competent members to engage in boundary spanning activities as they will maximize the cognitive benefits of EIS and finally minimize the cognitive dissimilarity between the boundary spanner and the rest of the group to facilitate the effective integration of novel insights into the group cognition.

This study is among the first empirical attempts to uncover the causal effect of EIS on knowledge elaboration and GCC in groups and to uncover the role of the boundary spanner in the EIS efforts.

The purpose of this paper is to study what extent readers’ socio-demographic characteristics, literary preferences and search behavior predict success in fiction search in library catalogs.

In total, 80 readers searched for interesting novels in four differing search tasks. Their search actions were recorded with a Morae Recorder. Pre- and post-questionnaires elicited information about their background, literary preferences and search experience. Readers’ literary preferences were grouped into four orientations by a factor analysis. Linear regression analysis was applied for predicting search success as measured by books’ interest scores.

Most literary orientations contributed to search success, but in differing search tasks. The role of result examination was greater compared to querying in contributing search success almost in each task. The proportion of variance explained in books’ interest scores varied between 5 (open-ended browsing) and 50 percent (analogy search).

The distribution of participants was biased toward females, and the results are aggregated within search session, both reducing the variation of the phenomenon observed.

This study is one of the first to explore how readers’ literary preferences and searching are associated with finding interesting novels, i.e. search success, in library catalogs. The results expand and support the findings in Mikkonen and Vakkari (2017) concerning associations between reader characteristics and fiction search success.

The purpose of this paper is to propose a scheme that allows users to interactively explore relations between entities in knowledge bases (KBs). KBs store a wide range of knowledge about real-world entities in a structured form as (subject, predicate, object). Although it is possible to query entities and relations among entities by specifying appropriate query expressions of SPARQL or keyword queries, the structure and the vocabulary are complicated, and it is hard for non-expert users to get the desired information. For this reason, many researchers have proposed faceted search interfaces for KBs. Nevertheless, existing ones are designed for finding entities and are insufficient for finding relations.

To this problem, the authors propose a novel “relation facet” to find relations between entities. To generate it, they applied clustering on predicates for grouping those predicates that are connected to common objects. Having generated clusters of predicates, the authors generated a facet according to the result. Specifically, they proposed to use a couple of clustering algorithms, namely, agglomerative hierarchical clustering (AHC) and CANDECOMP/PARAFAC (CP) tensor decomposition which is one of the tensor decomposition methods.

The authors experimentally show test the performance of clustering methods and found that AHC performs better than tensor decomposition. Besides, the authors conducted a user study and show that their proposed scheme performs better than existing ones in the task of searching relations.

The authors propose a relation-oriented faceted search method for KBs that allows users to explore relations between entities. As far as the authors know, this is the first method to focus on the exploration of relations between entities.

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.

The purpose of this paper is to identify and describe the influence of the knowledge base (KB) of the company on driving forces of innovation processes in knowledge-intensive services (KIS) and to compare the level of innovativeness of the final services.

The paper investigates through qualitative research 11 KIS organisations with different KB.

The research results identified and described the influence of the KB on driving forces of innovations processes and its results in companies with four newly identified KBs (analytical, synthetic, symbolic and compliance).

Further research, based on a larger number of companies, is needed to confirm the results of this research and to complement the effect of the KB on driving forces of innovation.

This research can help organisations understand how to develop strategic plans and new ideas for innovative services depending on the KB of the organisation.

The description of successful innovation processes and results in several leading companies presented in the study may help other companies in identifying knowledge-integration practices to improve performance and innovation processes that support multiplicity, productivity and creativity.

The study systemised the sources of new ideas for innovation in companies with different KB, several driving forces of innovation were identified and how these forces are affected by each KB; lastly, innovation results were compared in companies with different KB.

The purpose of this study is to critically review consumer knowledge in marketing and propose a future research agenda. Despite the many works that have examined this variable, given its strong influence on behaviour, it has generally been studied in association with other constructs, and no studies have focused on it in a specific way. Its definition, measurement and approaches to its role and usefulness are superficial and underdeveloped. After structuring and analysing the existing literature, the authors establish, (I) which aspects are of little use to the discipline, and (II) which research lines have the most potential and should be developed and studied in greater depth, to advance and complete the existing consumer knowledge framework.

A search was undertaken for documents in the main databases in which the term “consumer knowledge” appears in a marketing or consumer context, and a critical and reflexive approach was taken to analyse the main contributions and to structure them by content blocks.

Five main content blocks were identified. A set of research gaps were detected, mainly related to the lax conceptualisation of the topic, measurement problems and the scarcity of more useful works connected with business management, and several research lines are proposed that complement the existing framework to make it more complete and operational.

This paper offers a critical review and proposes a research agenda for one of the most used but little studied variables in the field of marketing, which may help academics and professionals in the discipline to continue developing useful theories and models.

El objetivo de este trabajo es revisar críticamente el conocimiento del consumidor en marketing y proponer una agenda de investigación futura. A pesar de los numerosos trabajos que han examinado esta variable, dada su fuerte influencia en el comportamiento, generalmente se ha estudiado en asociación con otros constructos, y ningún estudio se ha centrado en ella de manera específica. Su definición, medición y aproximaciones sobre su papel y utilidad son superficiales y poco desarrollados. Después de estructurar y analizar la literatura existente, establecemos (I) qué aspectos tienen poco uso para la disciplina y (II) qué líneas de investigación tienen más potencial y deben ser desarrolladas y estudiadas con mayor profundidad; para avanzar y completar el marco existente sobre conocimiento del consumidor.

Se realizó una búsqueda de documentos en las principales bases de datos en las que aparece el término “conocimiento del consumidor” en un contexto de marketing o consumo, y se adoptó un enfoque crítico y reflexivo para analizar las principales contribuciones y estructurarlas por bloques de contenido.

Se identificaron cinco bloques principales de contenido. Se detectó un conjunto de huecos de investigación, principalmente relacionados con la laxa conceptualización del tema, problemas de medición y la escasez de trabajos más útiles conectados con la gestión empresarial; y se proponen varias líneas de investigación que complementan el marco existente para hacerlo más completo y operativo.

Este documento ofrece una revisión crítica y propone una agenda de investigación para una de las variables más utilizadas pero poco estudiadas en el campo del marketing, lo que puede ayudar a académicos y profesionales en la disciplina a continuar desarrollando teorías y modelos útiles.

本文旨在对市场营销中的消费者知识进行批判性审视, 并提出未来的研究议程。虽然已有许多研究检验了该变量, 但由于其对行为产生强大影响, 通常会与其他结构变量一起研究, 而没有以特定方式专注于该变量。对其定义、测量以及其作用和用途的方法仍旧存在研究空白。通过对现有文献进行结构化分析后, 确定了以下两个方面：（I）哪些方面对该学科意义不大, （II）哪些研究方向最具研究潜力, 并且应该进一步深入发展和研究, 以推进和完善现有的消费者知识框架。

通过主要数据库检索市场营销或消费者背景下涉及“消费者知识”一词的文献, 采取批判性和反思性方法来分析其主要贡献, 并通过内容块对其进行结构化。

识别了五个主要内容块, 并发现存在一定程度的研究空白, 主要涉及该主题的概念松散化、测量问题以及与商业管理相关的有效研究的稀缺性。此外, 本文提出了几个研究线索, 这些线索为现有框架补充了信息, 使其更加完整且具备更强的操作性。

本文对市场营销领域中广泛使用但研究较少的变量进行了批判性评述, 并提出了相关研究议程。这一工作有助于学术界和专业人士继续发展实用的理论和模型。

Smart industry initiatives focus on intelligent and interconnected cyber-physical systems. These initiatives develop complex technical architectures that integrate heterogenous technologies, causing significant organizational complexity. Tapping into the digital capabilities of distant partners while capturing profit from such innovation is demanding. Furthermore, firms often need to establish and orchestrate inter-organizational collaborations without prior relations or established trust. As a result, smart industry initiatives bring together disparate organizational forms and institutional environments, distinctive knowledge bases, and geographically dispersed organizations. We conceptualize this organizational capability as ‘distant capabilities integration’. This research explores the governance mechanisms that support such integration and their relation to value capture. We analyse 11 IoT case studies organized in three categories (process, product and technologies) of smart industry initiatives. Building on existing literature, we consider different ways to describe distance, including knowledge heterogeneity and organizational, geographical, institutional, cultural and cognitive distance. Finally, we describe the governance mode appropriate for upstream (developing foundational technologies) and downstream (leveraging existing distant technologies) smart industry initiatives.