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This paper aims to propose a bed and breakfast (B&B) recommendation method that takes into account review timeliness and user preferences to help consumers choose the most satisfactory B&B.

This paper proposes a B&B ranking method based on improved intuitionistic fuzzy sets. First, text mining and cluster analysis are combined to identify the concerns of consumers and construct an attribute set. Second, an attribute-level-based text sentiment analysis is established. The authors propose an improved intuitionistic fuzzy set, which is more in line with the actual situation of sentiment analysis of online reviews. Next, subjective-objective combinatorial assignments are applied, considering the consumers’ preferences. Finally, the vlsekriterijumska optimizacija i kompromisno resenje (VIKOR) algorithm, based on the improved score function, is advised to evaluate B&Bs.

A case study is presented to illustrate the use of the proposed method. Comparative analysis with other multi-attribute decision-making (MADM) methods proves the effectiveness and superiority of the VIKOR algorithm based on the improved intuitionistic fuzzy sets proposed in this paper.

Proposing a B&B recommendation method that takes into account review timeliness and user customization is the innovation of this paper. In this approach, the authors propose improved intuitionistic fuzzy sets. Compared with the traditional intuitionistic fuzzy set, the improved intuitionistic fuzzy set increases the abstention membership, which is more in line with the actual situation of attribute-level sentiment analysis of online reviews.

Innovation is critical for businesses to stay competitive in today's world, as it allows them to constantly look for new ways to differentiate their products or services from their competitors as well as improve cost-effectiveness. This study explore the role of strategic human resource practices in developing organizations' competitive capabilities-differentiation and cost-effectiveness, which, improves their innovation performance to create a competitive advantage.

The authors collected data from 387 employees from 25 knowledge-intensive information technology organizations in India through a questionnaire-based survey. After checking for biases, reliability and validity, the hypothesized relationships were tested by structural equational modeling using AMOS 26.

Strategic HR practices have a significant and positive effect on innovation performance and both competitive capabilities-differentiation and cost-effectiveness. While the differentiation capability had a strong positive effect on innovation performance, cost-effectiveness capability was not significantly related to innovation performance. The differentiation capability mediates the relationship between strategic HR practices and innovation performance link, whereas the cost-effectiveness capability did not have a mediating effect.

This study provides practical insights to HR and knowledge managers to focus on development of human capital and invest in hiring, training, development, strategic performance management practices to enhance employees' knowledge behaviors, which, stimulates innovation performance.

The paper adds to the strategic HRM paradigm by clarifying the underlying process of how strategic HR practices leads to higher innovation. It affirms the vitality of choosing appropriate competitive capabilities, and supporting organizational factor for business's success. It fills an important research gap by providing original empirical evidence from knowledge intensive information technology organizations in the emerging economy of India.

The purpose of this study was to develop and test a research model that explored leader psychological capital (LPsyCap) as a predictor of follower creative performance (FCRP). The model also investigated follower job crafting (FJC) and follower knowledge collecting (FKC) and follower knowledge donating (FKD) behaviors as the multiple mediators of the trickle-down effect of LPsyCap on FCRP in a sequential manner.

Data were obtained from hotel employees in Korea. The hypotheses were tested using structural equation modeling with the user-defined estimands function.

LPsyCap boosted employees’ FCRP. FJC and FKC behaviors mediated the trickle-down effect of LPsyCap on FCRP in a sequential manner. As predicted, FKC behavior parallelly mediated the effect of FJC on FCRP.

Hotel firms should boost a workplace that would encourage employees to redefine and redesign their jobs. To achieve this, the presence of structural (e.g. learning new things in the workplace) and social (e.g. supervisor coaching) job resources and challenging job demands (e.g. willingly taking on additional tasks) would pay dividends.

This paper is one of its kind focusing on unexplored parallel and sequential multiple mediation effects that highlight FJC and FKC as the two potential mediators in the association between LPsyCap and FCRP.

For a better understanding of the preferences and differences of young consumers in emerging wine markets, this study aims to propose a clustering method to segment the super-new generation wine consumers based on their sensitivity to wine brand, origin and price and then conduct user profiles for segmented consumer groups from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences.

We first proposed a consumer clustering perspective based on their sensitivity to wine brand, origin and price and then conducted an adaptive density peak and label propagation layer-by-layer (ADPLP) clustering algorithm to segment consumers, which improved the issues of wrong centers' selection and inaccurate classification of remaining sample points for traditional DPC (DPeak clustering algorithm). Then, we built a consumer profile system from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences for segmented consumer groups.

In this study, 10 typical public datasets and 6 basic test algorithms are used to evaluate the proposed method, and the results showed that the ADPLP algorithm was optimal or suboptimal on 10 datasets with accuracy above 0.78. The average improvement in accuracy over the base DPC algorithm is 0.184. As an outcome of the wine consumer profiles, sensitive consumers prefer wines with medium prices of 100–400 CNY and more personalized brands and origins, while casual consumers are fond of popular brands, popular origins and low prices within 50 CNY. The wine sensory attributes preferred by super-new generation consumers are red, semi-dry, semi-sweet, still, fresh tasting, fruity, floral and low acid.

Young Chinese consumers are the main driver of wine consumption in the future. This paper provides a tool for decision-makers and marketers to identify the preferences of young consumers quickly which is meaningful and helpful for wine marketing.

In this study, the ADPLP algorithm was introduced for the first time. Subsequently, the user profile label system was constructed for segmented consumers to highlight their characteristics and demand partiality from three aspects: demographic characteristics, consumers' eating habits and consumers' preferences for wine attributes. Moreover, the ADPLP algorithm can be considered for user profiles on other alcoholic products.

This paper aims to investigate the role of organizational and technological enablers and their arrangement and alignment with the external environment to facilitate supply chain integration (SCI), which consequently improves operational performance.

The paper uses a structural equation modeling approach and the data from 307 manufacturing firms from the International Manufacturing Strategy Survey version VI for hypotheses testing.

The findings of the study reveal that (1) the alignment and particular arrangement of the sociotechnical organizational factors enable the SCI of a firm, (2) suitable organizational arrangements help in leveraging SCI under environmental pressures, and (3) SCI leverages the relationship between sociotechnical organizational factors and operational performance of the firm.

This paper informs managers that SCI leverages the operational performance of firms under heightened environmental pressures. Developing suitable manufacturing technologies infrastructure followed by organizational practices aligned with the manufacturing technologies make it easier to realize SCI.

This study explores the interaction of technological, organizational, and environmental factors as driving and enabling factors that help achieve SCI. Firms that develop an open and collaborative environment and use communication and integrative technologies to complement their work practices better cope with external pressures. These modern forms of working and the use of technologies facilitate SCI and leverage it effectively to positively impact firm performance.

Construction safety is a crucial aspect that has far-reaching impacts on economic development. But safety monitoring is often reliant on labor-based observations, which can be prone to errors and result in numerous fatalities annually. This study aims to address this issue by proposing a cloud-building information modeling (BIM)-based framework to provide real-time safety monitoring on construction sites to enhance safety practices and reduce fatalities.

This system integrates an automated safety tracking mobile app to detect hazardous locations on construction sites, a cloud-based BIM system for visualization of worker tracking on a virtual construction site and a Web interface to visualize and monitor site safety.

The study’s results indicate that implementing a comprehensive automated safety monitoring approach is feasible and suitable for general indoor construction site environments. Furthermore, the assessment of an advanced safety monitoring system has been successfully implemented, indicating its potential effectiveness in enhancing safety practices in construction sites.

By using this system, the construction industry can prevent accidents and fatalities, promote the adoption of new technologies and methods with minimal effort and cost and improve safety outcomes and productivity. This system can reduce workers’ compensation claims, insurance costs and legal penalties, benefiting all stakeholders involved.

To the best of the authors’ knowledge, this study represents the first attempt in Bangladesh to develop a mobile app-based technological solution aimed at reforming construction safety culture by using BIM technology. This has the potential to change the construction sector’s attitude toward accepting new technologies and cultures through its convenient choice of equipment.

Agriculture is the backbone of a country, contributing more than half of the sector of economy throughout the world. The need for precision agriculture is essential in evaluating the conditions of the crops with the aim of determining the proper selection of pesticides. The conventional method of pest detection fails to be stable and provides limited accuracy in the prediction. This paper aims to propose an automatic pest detection module for the accurate detection of pests using the hybrid optimization controlled deep learning model.

The paper proposes an advanced pest detection strategy based on deep learning strategy through wireless sensor network (WSN) in the agricultural fields. Initially, the WSN consisting of number of nodes and a sink are clustered as number of clusters. Each cluster comprises a cluster head (CH) and a number of nodes, where the CH involves in the transfer of data to the sink node of the WSN and the CH is selected using the fractional ant bee colony optimization (FABC) algorithm. The routing process is executed using the protruder optimization algorithm that helps in the transfer of image data to the sink node through the optimal CH. The sink node acts as the data aggregator and the collection of image data thus obtained acts as the input database to be processed to find the type of pest in the agricultural field. The image data is pre-processed to remove the artifacts present in the image and the pre-processed image is then subjected to feature extraction process, through which the significant local directional pattern, local binary pattern, local optimal-oriented pattern (LOOP) and local ternary pattern (LTP) features are extracted. The extracted features are then fed to the deep-convolutional neural network (CNN) in such a way to detect the type of pests in the agricultural field. The weights of the deep-CNN are tuned optimally using the proposed MFGHO optimization algorithm that is developed with the combined characteristics of navigating search agents and the swarming search agents.

The analysis using insect identification from habitus image Database based on the performance metrics, such as accuracy, specificity and sensitivity, reveals the effectiveness of the proposed MFGHO-based deep-CNN in detecting the pests in crops. The analysis proves that the proposed classifier using the FABC+protruder optimization-based data aggregation strategy obtains an accuracy of 94.3482%, sensitivity of 93.3247% and the specificity of 94.5263%, which is high as compared to the existing methods.

The proposed MFGHO optimization-based deep-CNN is used for the detection of pest in the crop fields to ensure the better selection of proper cost-effective pesticides for the crop fields in such a way to increase the production. The proposed MFGHO algorithm is developed with the integrated characteristic features of navigating search agents and the swarming search agents in such a way to facilitate the optimal tuning of the hyperparameters in the deep-CNN classifier for the detection of pests in the crop fields.

This paper aims to provide an integrated BIM-based approach for quantity take-off for progress payments in the context of high-rise buildings in Vietnam. It tries to find answers for the following questions: (1) When to start the QTO processes to facilitate the contract progress payments? (2) What information is required to measure the quantity of works to estimate contract progress payment (3) What are the challenges to manage (i.e. create, store, update and exploit)? What are the required information for this BIM use? and (4) How to process the information to deliver BIM-based QTO to facilitate contract progress payment?

The paper applied a deductive approach and expert consensus through a Delphi procedure to adapt to current innovation around BIM-based QTO. Starting with a literature review, it then discusses current practices in BIM-based QTO in general and high-rise building projects in particular. Challenges were compiled from the previous studies for references for BIM-based QTO to facilitate contract progress payment for high-rise building projects in Vietnam. A framework was developed considering a standard information management process throughout the construction lifecycle, when the BIM use of this study is delivered. The framework was validated with Delphi technique.

Four major challenges for BIM-based QTO discovered: new types of information required for the BIM model, changes and updates as projects progress, low interoperability between BIM model and estimation software, potentiality of low productivity and accuracy in data entry. Required information for QTO to facilitate progress payments in high-rise building projects include Object Geometric/Appearance Information, Structural Components' Definition and Contextual Information. Trade-offs between “Speed – Level of Detail–Applicable Breadth” and “Quality – Productivity” are proposed to consider the information amount to input at a time when creating/updating BIM objects. Interoperability check needed for creating, authoring/updating processing the BIM model's objects.

This paper is not flawless. The first limitation lies in that the theoretical framework was established only based on desk research and small number of expert judgment. Further primary data collection would be needed to determine exactly how the framework underlies widespread practices. Secondly, this study only discussed the quantity take-off specifically for contract progress payment, but not for other purposes or broader BIM uses. Further research in this field would be of great help in developing a standard protocol for automatic quantity surveying system in Vietnam.

A new theoretical framework for BIM-based QTO validated with Delphi technique to facilitate progress payments for high-rise building projects, considering all information management stages and the phases of information development in the project lifecycle. The framework identified four types of information required for this QTO, detailed considerations for strategies (Library Objects Development, BIM Objects Information Declaration, BIM-based QTO) for better managing the information for this BIM use. Two trade-offs of “Speed – LOD–Applicable Breadth” and “Quality – Productivity” have been proposed for facilitating the strategies and also for enhancing the total efficiency and effectiveness of the QTO process.

Organizations widely adopt knowledge management (KM) to develop and promote technologies and improve business effectiveness. Analytics can aid in KM, further augmenting company performance and decision-making. There has been significant research in the domain of analytics in KM in the past decade. Therefore, this paper aims to examine the current body of literature on the adoption of analytics in KM by offering prominent themes and laying out a research path for future research endeavors in the field of KM analytics.

A comprehensive analysis was conducted on a collection of 123 articles sourced from the Scopus database. The research has used a Latent Dirichlet Allocation methodology for topic modeling and content analysis to discover prominent themes in the literature.

The KM analytics literature is categorized into three clusters of research – KM analytics for optimizing business processes, KM analytics in the industrial context and KM analytics and social media.

Systematizing the literature on KM and analytics has received very minimal attention. The KM analytics view has been examined using complementary topic modeling techniques, including machine-based algorithms, to enable a more reliable, systematic, thorough and objective mapping of this developing field of research.

Managerial “awareness” of supply chain management (SCM) principles is a key antecedent of SCM adoption. However, supply chain awareness (SCA) provides fertile ground for further development. The authors combine extant research with the attention-based view of the firm to further develop SCA and theorize about its effect in an understudied context.

The authors combine SCA with supply chain orientation, of which awareness is central. The authors combine qualitative and archival data for a 10-year period to test SCA in nonprofits. SCA was measured unobtrusively to avoid respondent bias; then, the authors explore how SCA relates to revenue generation from services provided.

SCA correlates positively with revenue generation. Drawing on a contingency perspective, the authors test two moderators relevant to nonprofits. The positive effect of SCA on revenue is stronger for nonprofits collocated in cities with corporate headquarters but weaker for those with larger boards.

The study further advances the notion of awareness for studying SCM phenomena and provides evidence of its relevance in the unexamined context of human services nonprofit organizations (NPOs). This work has implications for how attention to SCM principles shapes organizational outcomes, the factors that moderate these relationships and the importance of unobtrusively measuring awareness in SCM research. The authors used WayBack Machine to harvest websites. However, the quality and depth of text obtained prior to 2008 were lower than those of later years. Additionally, archival data for NPOs are limited.

Findings inform about the fit between nonprofit resources, type of board and fit with how to fund operations. This research provides an alternative way for policy makers to assess NPO capacity by focusing on the fundamental SCM concepts.

The authors contribute to the dialogue about NPOs developing financial independence through revenue generation from services sold to end customers.

NPOs are seldom studied in SCM. This is an attempt to study NPOs by combining qualitative and quantitative data.