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This study investigates shifts in luxury consumers' perceptions regarding luxury consumption, subsequent changes in the meaning of luxury and antecedents of luxury observed amidst the COVID-19 pandemic.

Overall, 145, one-to-one qualitative interviews were conducted online with luxury consumers and the data acquired was analysed using NVivo.

Phygital connectedness and access-based consumption are the future of luxury for luxury consumers' well-being, social connectedness, living experience and rational and thoughtful luxury consumption. Moreover, distinct luxury symbols (e.g. conciseness towards societal connotation of luxury goods and consumption, empathy, wisdom and maturity) and transformation expectations (for the self, others in society and luxury brands) govern luxury consumption behaviour.

The meaning of luxury amidst the pandemic is explained along a continuum, from luxury transforming consumers' inner selves to influencing other consumers' lives to transforming society.

Luxury professionals should include phygital experience, sustainability, social–cultural sensitivity, empathy, symbolism, mindfulness and thoughtfulness in marketing strategies.

New perspectives have enriched the realm of luxury.

The purpose of this paper is to develop a scale for measuring consumer doubt toward new products.

The scale was developed in several steps. A large pool of items to represent consumer doubt was generated. Experts reviewed the scale items for conciseness and clarity. An exploratory factor analysis to examine the unidimensionality, convergent validity, and discriminant validity of each construct was conducted. The model was then validated using partial least squares modeling. Finally, the scale and its form were validated, and potential response biases assessed. Data from three studies were used.

The results show that by focusing on reasons for deference, rather than acceptance, the scale yields new insight into innovation success and failure. The CDNP scale is a reliable and valid measurement instrument to assess consumer doubt toward new products.

For researchers, the results show that only considering positive aspects on innovation adoption can lead to only a partial understanding of how innovation diffuses in the market.

By overcoming consumer doubt at early stages of innovation launch, companies could overcome problems related to innovation failure.

The literature on innovation adoption has almost exclusively focused on why innovations succeed by examining consumer acceptance of innovations. Yet, a potentially more serious issue that would need to be tackled is why innovations fail. This paper focuses on consumer doubt toward new products, i.e. a lack of conviction that a new product will fulfill its promises. Three studies show that the scale of consumer doubt is valid, and it provides new insights into innovation adoption.

Large collections of patent documents disclosing novel, non-obvious technologies are publicly available and beneficial to academia and industries. To maximally exploit its potential, searching these patent documents has increasingly become an important topic. Although much research has processed a large size of collections, a few studies have attempted to integrate both patent classifications and specifications for analyzing user queries. Consequently, the queries are often insufficiently analyzed for improving the accuracy of search results. This paper aims to address such limitation by exploiting semantic relationships between patent contents and their classification.

The contributions are fourfold. First, the authors enhance similarity measurement between two short sentences and make it 20 per cent more accurate. Second, the Graph-embedded Tree ontology is enriched by integrating both patent documents and classification scheme. Third, the ontology does not rely on rule-based method or text matching; instead, an heuristic meaning comparison to extract semantic relationships between concepts is applied. Finally, the patent search approach uses the ontology effectively with the results sorted based on their most common order.

The experiment on searching for 600 patent documents in the field of Logistics brings better 15 per cent in terms of F-Measure when compared with traditional approaches.

The research, however, still requires improvement in which the terms and phrases extracted by Noun and Noun phrases making less sense in some aspect and thus might not result in high accuracy. The large collection of extracted relationships could be further optimized for its conciseness. In addition, parallel processing such as Map-Reduce could be further used to improve the search processing performance.

The experimental results could be used for scientists and technologists to search for novel, non-obvious technologies in the patents.

High quality of patent search results will reduce the patent infringement.

The proposed ontology is semantically enriched by integrating both patent documents and their classification. This ontology facilitates the analysis of the user queries for enhancing the accuracy of the patent search results.

The purpose of this paper is to examine the potential for eXtensible Business Reporting Language (XBRL) to go beyond static reporting. A taxonomy structure of information is developed for providing a knowledge base and insights for an XBRL taxonomy for integrated reporting (IR).

Design Science (DS) research, as a pragmatic exploratory research approach, is embraced to create a new “artefact” and thematic content analysis is used to analyse IR in practice.

Using XBRL for IR allows a shift from static and periodic reporting to more relevant and dynamic corporate disclosure for stakeholders, who can navigate and retrieve customised disclosure information according to their interest by exploiting the multidimensionality of IR and overcome some of its criticisms. The bi-dimensional taxonomy structure the authors’ present allows users to navigate disclosure from two different perspectives (content elements (CE) and capitals), display specific themes of interest, and drill down to more detailed information. Because of its evidence-based nature and levels of disaggregation, it provides flexibility to preparers and users of information. Additionally, the findings demonstrate the need to codify sector-specific information for the CE, so that to direct the efforts toward the development of sector-specific taxonomy extensions in developing an XBRL taxonomy for IR.

The limitations of DS research are, first, the artefact design and, second, its effects in practice. The first limitation stems from the social actors’ perspective taken into account to develop the taxonomy structure, which derives from the analysis of the reporting practices rather than a pluralistic approach and dialogic engagement. The second limitation relates to the XBRL taxonomy development process because, since the study is limited to the “design” phase being codification and structuring the knowledge base for an XBRL taxonomy, there is a need to develop a taxonomy in XBRL and then apply it in practice to empirically demonstrate the potential and benefits of XBRL in the IR context.

The taxonomy structure is targeted at entities interested in designing an XBRL taxonomy for IR. This is a call for academics and practitioners to explore the potential of technology to improve corporate disclosure and open up new projections for resurging themes on intellectual capital (IC) reporting with prospects for IC “fourth-stage” research focused on IC disclosure.

This is an interdisciplinary research employing the DS approach, which is rooted in information systems research. It is the first academic study providing pragmatic results for using XBRL in the context of IC and IR.

Prime contractors spend up to 90 per cent of a construction project's turnover on buying goods and services, and thus suppliers have a large impact on project performance. Therefore, the purchasing function management of the prime contractor has a large influence on the overall performance: the more developed (i.e. mature or professional) this function is, the greater its positive contribution. The purpose of this paper is to develop and test a quick scan purchasing maturity tool by applying a design science research method.

The maturity tool is developed by applying Hevner's framework for design science research. In this framework, foundations drawn from the available knowledge base are used to develop the new tool. Scientific justification of this new tool and approval of its approach for construction practice is obtained through testing it in the specific context of a case company.

The tool provides a company with insight into its current level of purchasing maturity and possibilities for improving performance by increasing this level.

The conciseness and the limited time required to use the tool are major advantages over existing alternatives for construction practice.

For the last several decades, technology has been playing an important role in changing the lives of consumers with an unexpected speed of innovative developments. Most of them were disruptive and had shaped not only the behaviour of consumers, but also empowered them to search for better products and services. These changes took place in media, communication, and information management of socialisation and collaboration. The digitisation revolution is a continuum until people and machines embrace a common ground for improving the lives of consumers. There were three stages of this movement. In the first stage, Turkish perspective was in alignment with the world where new channels of communication were established with support of Internet and information management. Marketing technology tools such as customer relationship management and call centre systems were discovered. In the second stage, continuous learning from the best uses and implementations has started. The ultimate goal became total customer satisfaction. Many improvements and innovative services, such as omni-channel marketing, took place for achieving this goal. Today, in the third stage, new marketing tools are being developed on the basis of integrated machine learning, such as analysis of customer conciseness, prediction of behaviour and perceptive marketing, which will be used extensively through digital platforms, new media, social web and in everyday devices for targeted marketing. In this chapter, a broader look is taken and an explanation is made for what has happened through these periods of intersection of marketing science and information technology. Moreover, ongoing changes which have given a new impetus to consumer life are addressed with respect to marketing management literature.

This study explores whether and how four main factors of short-branded video content (content matching, information relevance, storytelling and emotionality) facilitate consumer engagement (likes, comments and shares), as well as the moderating effect of the release time (morning, afternoon and evening) in such relationships.

This study uses Python to write programs to crawl relevant data information, such as consumer engagement and short video release time. It combines coding methods to empirically analyze the impact of short-branded video content characteristics on consumer engagement. A total of 10,240 Weibo short videos (total duration: 238.645 h) from 122 well-known brands are utilized as research objects.

Empirical results show that the content characteristics of short videos significantly affected consumer engagement. Furthermore, the release time of videos significantly moderated the relationship between the emotionality of short videos and consumer engagement. Content released in the morning enhanced the positive impact of warmth, excitement and joy on consumer engagement, compared to that released in the afternoon.

The findings provide new insights for the dissemination of products and brand culture through short videos. The authors suggest that enterprises that use brand videos consider content matching, information relevance, storytelling and emotionality in their design.

From a broader perspective, this study constructs a new method for comprehensively evaluating short-branded video content, based on four dimensions (content matching, information relevance, storytelling and emotionality) and explores the value of these dimensions for creating social media marketing success, such as via consumer engagement.

The paper examines integrated reporting (IR) practices of two Japanese universities and three South African universities by evaluating and comparing their 2019 integrated reports.

A multiple case study research method is used in this study.

The paper reveals that IR is in its infancy at the sample universities. Some universities have initiated disclosing information to their stakeholders on how they create value. However, the universities lack a comprehensive approach to integrating financial and non-financial information, thereby affecting the IR disclosure quality. The findings indicate that informal coercive pressure of South African universities is a primary driving factor that enables the universities to achieve a higher IR disclosure quality than their Japanese counterparts.

This paper argues that institutional theory is relevant for explaining the differences in IR practices of the universities in the two different jurisdictional settings.

The research will be of interest to university administrators, policymakers, regulators and other stakeholder groups of universities. The assessment of integrated reports serves as a first step to help the universities improve IR practices as well as to facilitate the diffusion of IR in higher education institutions (HEIs) globally. There is also a need for universities to pay more attention to the storytelling of their value creation in future IR disclosures.

It is the first to assess the IR quality of the Japanese sample universities as well as the first to conduct a comparative analysis for IR practices of universities in two different jurisdictional settings that have adopted IR. The findings of this study add to the current scholarly debate on universities' ability to tell their stories on their value creation to stakeholders via integrated reports.

This article aims to introduce practical based criteria for effective organizational communication.

The subject scope for this article is corporate communication. The study is based on literature reviews and a qualitative study, entailing the basic principles of the phenomenological approach, with 20 subjects.

Four additional criteria for effective corporate communication surfaced: responsible; professional; concise; and sincere.

The studies reviewed, although in‐depth, apply to a small sample in one metropolitan environment, which makes generalization among different cultures riskier.

Organizational managers may use these findings to reflect on their communication strategies and improve them, where necessary, on the basis of the findings of this study.

The paper's value lies in the four additional criteria found as a result of reflections from members of the corporate workforce, after having been exposed to a course on organizational communication, and therefore, existing criteria in literature. The additional criteria may be considered important for corporate workers, and should therefore not be ignored by managers.

The historical data usually consist of overlapping reports, and these reports may contain inconsistent data, which may return incorrect results of a query search. Moreover, users who issue the query may not learn of this inconsistency even after a data cleaning process (e.g. schema matching or data screening). The inconsistency can exist in different types of data, such as temporal or spatial data. Therefore, this paper aims to introduce an information fusion method that can detect data inconsistency in the early stages of data fusion.

This paper introduces an information fusion method for multi-robot operations, for which fusion is conducted continuously. When the environment is explored by multiple robots, the robot logs can provide more information about the number and coordination of targets or victims. The information fusion method proposed in this paper generates an underdetermined linear system of overlapping spatial reports and estimates the case values. Then, the least squares method is used for the underdetermined linear system. By using these two methods, the conflicts between reports can be detected and the values of the intervals at specific times or locations can be estimated.

The proposed information fusion method was tested for inconsistency detection and target projection of spatial fusion in sensor networks. The proposed approach examined the values of sensor data from simulation that robots perform search tasks. This system can be expanded to data warehouses with heterogeneous data sources to achieve completeness, robustness and conciseness.

Little research has been devoted to the linear systems for information fusion of tasks of mobile robots. The proposed information fusion method minimizes the cost of time and comparison for data fusion and also minimizes the probability of errors from incorrect results.