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The purpose of this paper is to introduce a new similarity method to gauge the differences between two subject hierarchical structures.

In the proposed similarity measure, nodes on two hierarchical structures are projected onto a two-dimensional space, respectively, and both structural similarity and subject similarity of nodes are considered in the similarity between the two hierarchical structures. The extent to which the structural similarity impacts on the similarity can be controlled by adjusting a parameter. An experiment was conducted to evaluate soundness of the measure. Eight experts whose research interests were information retrieval and information organization participated in the study. Results from the new measure were compared with results from the experts.

The evaluation shows strong correlations between the results from the new method and the results from the experts. It suggests that the similarity method achieved satisfactory results.

Hierarchical structures that are found in subject directories, taxonomies, classification systems, and other classificatory structures play an extremely important role in information organization and information representation. Measuring the similarity between two subject hierarchical structures allows an accurate overarching understanding of the degree to which the two hierarchical structures are similar.

Both structural similarity and subject similarity of nodes were considered in the proposed similarity method, and the extent to which the structural similarity impacts on the similarity can be adjusted. In addition, a new evaluation method for a hierarchical structure similarity was presented.

This paper examines how a firm's hierarchical complexity, which is determined by the way it organizes its subsidiaries across the hierarchical levels, can impact its stock price crash risk.

The authors employ a measure of hierarchical complexity that captures the depth and breadth of how subsidiaries are organized within a firm. This measure is calculated using information about firms' subsidiaries extracted from the Bureau van Dijk (BvD) database that allows the authors to construct each firm's hierarchical structure. The data sample includes 2,461 USA firms for the period from 2012 to 2017 (11,006 firm-year observations). Univariate tests and panel regression are used for the main analysis. Two-stage-least-squares (2SLS) instrumental variable regression and various other tests are employed for robustness check.

The results show a positive relationship between hierarchical complexity and stock price crash risk. This relationship is amplified in firms with a greater number of subsidiaries that are hierarchically distanced from the parent company as well as in firms with a greater number of foreign subsidiaries in countries with weaker rule of law.

This paper is the first to investigate the impact hierarchical complexity has on crash risk. The results highlight the role that a firm's organizational structure can have on asset pricing behavior.

Further understanding of structural hierarchy is critically needed to assess the usefulness of different alliance structures. This study goes beyond transaction cost reasoning and incorporates social exchange theoretic perspective with the aim of capturing the concurrent relationships of alliance type and specific alliance experience with hierarchy of alliance structure.

Logistic regression analysis of data on 402 strategic alliances is used to test the two hypotheses advanced in the paper.

The social‐exchange‐based hypothesis is supported – specific alliance experience is negatively related to hierarchy of alliance structure. The transaction‐cost‐based hypothesis is not supported – hierarchy of alliance structure is not greater in horizontal alliances than in vertical alliances.

Strategic alliances with different purposes, such as R&D, supply procurement, marketing, co‐production, and co‐development, may have different industry norms of structuring alliances. This study does not account for these underlying differences within strategic alliances.

The social exchange theory‐based variable (i.e. specific alliance experience) has a more salient influence on alliance structure than does the transaction cost‐based variable (i.e. alliance type). The findings signal the relative importance of communal harmony compared to competitive rivalry.

The paper shows that results suggest that high bureaucratic costs of more hierarchical structures diminish the transaction cost economizing benefits of such structures. This is especially the case when alliances are not expected to experience very high levels of relational hazards (usually in vertical alliances). It appears that partnering firms' concerns with high bureaucratic costs may at times exceed the marginal benefits of control and coordination of exceedingly hierarchical alliance structures.

This paper aims to investigate how organizational structure (i.e. centralized hierarchical vs decentralized egalitarian decision-making) can color leadership evaluations of equivalently positioned men and women independent of their actual leadership style. This study addresses three questions: Are men’s leadership abilities, in terms of competence, dominance and interpersonal skills, evaluated more positively than women when they lead a hierarchical company? Are men and women’s leadership abilities evaluated similarly when they lead an egalitarian company? Do organizational outcomes change these effects?

The research performs an eight-condition online vignette experiment on American community college students.

The findings suggest that organizational structure and outcomes influence how male versus female leaders are perceived. When leading a hierarchical company, male leaders not only gain more in perceived leadership ability when their company succeeds but are also less likely to lose legitimacy when their company fails. When leading successful egalitarian organizations, men and women’s leadership skills are thought to gain similar legitimacy, but when an egalitarian organization fails, perceptions of female leaders’ competence, status dominance and interpersonal skills drop more than those of men.

This study’s generalizablity is limited given the sample of participants and the context of the industry utilized in the vignette.

This study suggests that women’s promotion into leadership can be impeded by the decision-making structure of the organizations they lead independent of their individual choice in management style. Women leaders face not only disadvantaged evaluations of their leadership abilities in hierarchical organizations but are also not unilaterally advantaged in egalitarian organizations.

This paper highlights the need to theoretically examine how organizational structures fundamentally embed gender stereotypes.

In this study, the authors unpack the micro-level processes of knowledge accumulation (experiential learning) and knowledge application (problem solving) to examine how task allocation structures influence organizational learning. The authors draw on untapped potential of the classical garbage can model (GCM), and extend it to analyze how restrictions on project participation influence differentiation and integration of organizational members’ knowledge and consequently organizational efficiency in solving the diverse, changing problems from an uncertain task environment. To isolate the effects of problem or knowledge diversity and experiential learning, the authors designed three simulation experiments to identify the most efficient task allocation structure in conditions of (1) knowledge homogeneity, (2) knowledge heterogeneity, and (3) experiential learning. The authors find that free project participation is superior when the members’ knowledge and the problems they solve are homogenous. When problems and knowledge are heterogeneous, the design requirement is on matching specialists to problem types. Finally, the authors found that experiential learning creates a dynamic problem where the double duty of adapting the members’ specialization and matching the specialists to problem types is best solved by a hierarchic structure (if problems are challenging). Underlying the efficiency of the hierarchical structure is an adaptive role of specialized members in organizational learning and problem solving: their narrow but deep knowledge helps the organization to adapt the knowledge of its members while efficiently dealing with the problems at hand. This happens because highly specialized members reduce the necessary scope of knowledge and learning for other members during a certain period of time. And this makes it easier for the generalists and for the organization as a whole, to adapt to unforeseen shifts in knowledge demand because they need to learn less. From this nuanced perspective, differentiation and integration may have a complementary, rather than contradictory, relation under environmental uncertainty and problem diversity.

Motivated to know more about the internal means through which accountability for sustainability takes shape within organisations (in what ways and by whom), this paper aims to explore how accountability for sustainability is constructed within an organisation during a process of establishing a control system for sustainability.

This paper adopts a qualitative case study approach of a decentralised industrial group, operating mainly in Scandinavia, between 2017 and 2020. Both primary and secondary data are used (e.g. document analyses, semi-structured interviews, informal conversations and site visits) to inform the findings and analysis.

The findings reveal a multi-faceted path towards accountability for sustainability that involves several concerns and priorities at organisational and individual levels, resulting in a separate sustainability control systems within each subsidiary company. Although hierarchical structures for accountability exist, socialising accountability activities are needed to (further) mobilise sustainable accounts.

Successful sustainable control systems require employees making sense of formalised accountability instruments (e.g. policies and procedures) to establish their roles and responsibilities in organisations.

This paper proposes socialisation processes as important for driving forward sustainability solutions.

This study elaborates on the internal accountability dynamic for the construction of sustainable accounts. Its novelty is built upon the interaction of hierarchical and socialising accountability forms as necessary for establishing a control system for sustainability. It furthermore illustrates the relationship between the external and internal pathways of accountability.

Browsing knowledge documents in a peer-to-peer (P2P) environment is difficult because knowledge documents in such an environment are large in quantity and distributed over different peers who organize the documents according to their own views. This paper aims to propose a method for constructing a personal knowledge map for a peer to facilitate knowledge browsing and alleviate information overload in P2P environments.

The research presents a method for constructing a personal knowledge map. The method adopts an ontology-concept-tree-based classification algorithm to recognize a peer’s personal knowledge structure and construct a personal knowledge map, and uses a self-organizing map algorithm to cluster and visualize the knowledge documents. The correctness of the created knowledge map is evaluated with a collection of abstracts of academic papers.

The method for constructing a personal knowledge map is the main finding of this research. The evaluation shows that the created knowledge map is good in quality.

The proposed method provides a way for P2P platforms to understand their users’ knowledge background, as well as to improve the P2P platform environment. However, the proposed method will not help a peer when he has nothing in his individual knowledge document repository (i.e. the “cold start” problem). The method also requires a relatively good ontology base for a P2P document sharing system to use the method effectively.

It is novel that the proposed method organizes the knowledge documents related to a peer’s knowledge background into a personal knowledge map. Moreover, the created knowledge map combines the advantages of a hierarchical display and a map display. It has values for a distributed P2P environment to facilitate users’ knowledge browsing and to alleviate information overload.

This study aims to develop a hierarchical topic analysis tool (HTAT) based on hierarchical Latent Dirichelet allocation (hLDA) to support digital humanities research that is associated with the need of topic exploration on the Digital Humanities Platform for Mr. Lo Chia-Lun’s Writings (DHP-LCLW). HTAT can assist humanities scholars on distant reading with analysis of hierarchical text topics, through classifying time-stamped texts into multiple historical eras, conducting hierarchical topic modeling (HTM) according to the texts from different eras and presenting through visualization. The comparative network diagram is another function provided to assist humanities scholars in comparing the difference in the topics they wish to explore and to track how the concept of a topic changes over time from a particular perspective. In addition, HTAT can also provide humanities scholars with the feature to view source texts, thus having high potential to be applied in promoting the effectiveness of topic exploration due to simultaneously integrating both the topic exploration functions of distant reading and close reading.

This study adopts a counterbalanced experimental design to examine whether there is significant differences in the effectiveness of topic inquiry, the number of relevant topics inquired and the time spent on them when research participants were alternately conducting text exploration using DHP-LCLW with HTAT or DHP-LCLW with Single-layer Topic Analysis Tool (SLTAT). A technology acceptance questionnaire and semi-structured interviews were also conducted to understand the research participants' perception and feelings toward using the two different tools to assist topic inquiry.

The experimental results show that DHP-LCLW with HTAT could better assist the research participants, in comparison with DHP-LCLW with SLTAT, to grasp the topic context of the texts from two particular perspectives assigned by this study within a short period. In addition, the results of the interviews revealed that DHP-LCLW with HTAT, in comparison with SLTAT, was able to provide a topic terms that better met research participnats' expectations and needs, and effectively guided them to the corresponding texts for close reading. In the analysis of technology acceptance and interview data, it can be found that the research participants have a high and positive tendency toward using DHP-LCLW with HTAT to assist topic inquiry.

The Jieba Chinese word segmentation system was used in the Mr. Lo Chia-Lun’s Writings Database in this study, to perform word segmentation on Mr. Lo Chia-Lun’s writing texts for topic modeling based on hLDA. Since Jieba word segmentation system is a lexicon based word segmentation system, it cannot identify new words that have still not been collected in the lexicon well. In this case, the correctness of word segmentation on the target texts will affect the results of hLDA topic modeling, and the effectiveness of HTAT in assisting humanities scholars for topic inquiry.

An HTAT was developed to support digital humanities research in this study. With HTAT, DHP-LCLW provides hmanities scholars with topic clues from different hierarchical perspectives for textual exploration, and with temporal and comparative network diagrams to assist humanities scholars in tracking the evolution of the topics of specific perspectives over time, to gain a more comprehensive understanding of the overall context of the texts.

In recent years, topic analysis technology that can automatically extract key topic information from a large amount of texts has been developed rapidly, but the topics generated from traditional topic analysis models like LDA (Latent Dirichelet allocation) make it difficult for users to understand the differences in the topics of texts with different hierarchical levels. Thus, this study proposes HTAT which uses hLDA to build a hierarchical topic tree with a tree-like structure without the need to define the number of topics in advance, enabling humanities scholars to quickly grasp the concept of textual topics and use different hierarchical perspectives for further textual exploration. At the same time, it also provides a combination function of temporal division and comparative network diagram to assist humanities scholars in exploring topics and their changes in different eras, which helps them discover more useful research clues or findings.

Potential and benefits of classification schemes and thesauri in building organizational taxonomies cannot be fully utilized by organizations. Empirical data of building an organizational taxonomy by the top‐down approach of using classification schemes and thesauri appear to be lacking. The paper seeks to make a contribution in this regard.

A case study of building an organizational taxonomy was conducted in the information studies domain for the Division of Information Studies at Nanyang Technology University, Singapore. The taxonomy was built by using the Dewey Decimal Classification, the Information Science Taxonomy, two information systems taxonomies, and three thesauri (ASIS&T, LISA, and ERIC).

Classification schemes and thesauri were found to be helpful in creating the structure and categories related to the subject facet of the taxonomy, but organizational community sources had to be consulted and several methods had to be employed. The organizational activities and stakeholders' needs had to be identified to determine the objectives, facets, and the subject coverage of the taxonomy. Main categories were determined by identifying the stakeholders' interests and consulting organizational community sources and domain taxonomies. Category terms were selected from terminologies of classification schemes, domain taxonomies, and thesauri against the stakeholders' interests. Hierarchical structures of the main categories were constructed in line with the stakeholders' perspectives and the navigational role taking advantage of structures/term relationships from classification schemes and thesauri. Categories were determined in line with the concepts and the hierarchical levels. Format of categories were uniformed according to a commonly used standard. The consistency principle was employed to make the taxonomy structure and categories neater. Validation of the draft taxonomy through consultations with the stakeholders further refined the taxonomy.

No similar study could be traced in the literature. The steps and methods used in the taxonomy development, and the information studies taxonomy itself, will be helpful for library and information schools and other similar organizations in their effort to develop taxonomies for organizing content and aiding navigation on organizational sites.

This paper aims to outline the fundamental assumptions regarding the laddering methodology (Reynolds and Gutman), examine how some “hard” laddering approaches meet or violate these assumptions, provide a review and comparison of a series of studies using “soft” and “hard” laddering approaches to examine the hierarchical structure of means‐end theory, and assess if the discrepant conclusions from this series of studies may be attributed to violations of the fundamental assumptions of the laddering methodology.

A series of published empirical works using “hard” and “soft” laddering approaches, which aim to examine the hierarchical structure of means‐end theory (Gutman), are reviewed and compared to integrate research findings and to examine discrepancies. Discrepant conclusions, which appear to be attributable to violations of the assumptions underlying the laddering methodology, are explored through a reanalysis and reclassification of the content codes.

The paper validates the case for laddering and the care needed to gauge how conclusions can be affected when violations of fundamental assumptions of the laddering methodology occur.

Means‐end chain research and, more specifically, the laddering methodology are in need of investigations that assess the importance of its underlying assumptions. Additional work validating both the “hard” and “soft” laddering approaches is also needed.

Results of means‐end research are more interpretable and less ambiguous when the fundamental assumptions of the laddering methodology are met. In practice, means‐end theory benefits managers by providing a useful structure to aid in the interpretation of laddering data.

This paper outlines the fundamental assumptions regarding the laddering methodology to provide methodological guidelines for laddering researchers. This paper also reviews the academic literature examining the hierarchical structure of means‐end theory and explores how violations of the fundamental assumptions of the laddering methodology may impact research findings.