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Market evaluation of products is the basis for product innovation, yet traditional expert-based evaluation methods are highly dependent on the specialization of experts. There exist a lot of weak expert-generated texts on the Internet of their own subjective evaluations of products. Analyzing these texts can indirectly extract the opinions of weak experts and transform them into decision-support information that assists product designers in understanding the market.

In social networks, a subset of users, termed “weak experts”, possess specialized knowledge and frequently share their product experiences online. This study introduces a comparative opinion mining framework that leverages the insights of “weak experts” to analyze user opinions.

An automotive product case study demonstrates that evaluations based on weak expert insights offer managerial insights with a 99.4% improvement in timeliness over traditional expert analyses. Furthermore, in the few-shot sentiment analysis module, with only 10% of the sample, the precision loss is just 1.59%. In addition, the quantitative module of specialization weighting balances low-specialization expert opinions and boosts the weight of high-specialization weak expert views. This new framework offers a valuable tool for companies in product innovation and market strategy development.

This study introduces a novel approach to opinion mining by focusing on the underutilized insights of weak experts. It combines few-shot sentiment analysis with specialization weighting and AHP, offering a comprehensive and efficient tool for product evaluation and market analysis.

Currently, there is a dearth of research studies regarding macro analysis of the workforce productivity of the US construction industry. The purpose of this paper is to calculate the workforce productivity changes of the US construction industry from 2006 to 2016, with the number of laborers as input and value of construction industry as output.

The present study introduced the data envelopment analysis (DEA) based Malmquist productivity index model to measure the workforce productivity of the US construction industry from 2006 to 2016.

The results indicated that the workforce productivity of the US construction industry experienced a continuous decline, except for the increases from 2011 to 2013 and from 2014 to 2015. It was also shown that there were gaps in the workforce productivity development level among all states and nine regions in the US construction industry. Besides, the relationship between workforce productivity and four aspects, including real estate price, workforce, climate distribution and economic factors, was analyzed.

The calculation of the productivity of the US construction industry is based on the premise that the external environment is fixed and unchanged from 2006 to 2016, but the multi-level DEA model for further calculation is required for obtaining more effective conclusions.

This paper measures the workforce productivity of the US construction industry over the past 11 years, which added latest analysis and knowledge into the construction industry, providing decision-makers with advice and data support to formulate policies to improve workforce productivity.

This study provided both government decision-makers and industrial practitioners with important macro background environment information, which will facilitate the improvement of workforce productivity in the construction industry in different regions of the US.

Openness to external knowledge has recently gained popularity as a means for firms to complement and leverage internal knowledge in the pursuit of innovation outcomes. However, conflicting evidence exists regarding the role of openness in external knowledge acquisition. This paper aims to propose that openness to external knowledge has a nonlinear effect on innovation performance and that this nonlinear relationship is contingent on an ambidextrous knowledge search strategy.

Based on original large-scale survey of 246 interfirm collaborations in the high-technology industry, it is found that the impact of openness to external knowledge on innovation performance exhibits an inverted-U shape and that this relationship is affected by an ambidextrous knowledge search strategy.

The results indicate that an ambidextrous knowledge strategy that addresses the depth and breadth of external knowledge significantly influences a firm’s ability to derive benefits from increased openness to external knowledge. Empirically, the authors provide an original contribution to high-technology firms by exploring how and why an ambidextrous knowledge strategy can be a critical catalyst spurring innovation performance.

The research scope is limited to a single industry. Further research could extend the theoretical framework to multiple industries, which may increase the likelihood of innovation theory development.

The results suggest that firms opening up the boundaries of their innovation activity to engage in external knowledge are able to leverage their in-house innovation to enhance their innovation performance. The authors advocate that in innovation management domains, greater emphasis is needed on how openness to external knowledge has more positive impacts not only on innovation performance but also on innovation implemented management.

This study is among the first to investigate the ambidextrous knowledge search effect on the external knowledge of high-technology firms. This paper contributes to the theoretical and practical literature concerning openness innovation and knowledge management by reflecting on the ambidextrous knowledge search strategy.

Previous studies have discussed individual effects that certain agritourism activities have on visitor response while ignoring interaction effects. Therefore, the purpose of this study is to discuss both the individual and interaction effects of agritourism activities on tourist revisit intention.

This study classified agritourism activities into four categories and collected 883 valid samples. Logistic regression was then applied to test the influence of agritourism activities on tourist revisit intention.

Based on the results of the statistical analysis, it was found that those agritourism activities, which required mutual cooperation such as do-it-yourself (DIY), animal interaction/feeding and fruit and vegetable picking, enhanced tourist revisit intention. Furthermore, the agritourism groups participating in activities with or without children did not have consistent revisit intentions regarding animal feeding/interaction activities. In particular, this study found that willingness to revisit for tourists with children was influenced by animal feeding/interaction, but not for tourists without children.

This study demonstrates that not all agritourism activities enhance revisit intention. For this reason, agritourism businesses should consider redesigning their activities related to visitor and animal interactions as increasing conscientiousness regarding animal welfare, especially with regard to animal abuse. Additionally, those activities focused on education and ecology are not as appreciated by tourists as they may have been previously assumed between different groups.

The findings of this study reveal that if the types of agritourism activities could fulfill visitors' expectations and desires they are more likely to have a satisfying experience. The authors consider some of these notions to be a kind of unrealistic fantasy regarding agritourism and the kind of activities involved therein. This kind of fantasy is likely formed by visitors 2019 past experiences and culture. As a result, the authors conclude that agritourism activities focused on the education of plants and ecology do not achieve the truly preferred aim of better interaction between people.

农业观光：体验设计、活动及再游意愿摘要

先前研究讨论农业观光活动的各别效果对游客反应的影响, 却忽略了交互作用。因此, 本研究目的为讨论农业观光活动的各别及交互效果对游客再游意愿的影响。

本研究将农业观光活动分为四类并收集883份有效问卷, 应用逻辑回归以检测农业观光活动对游客再游意愿的影响。

根据统计分析结果, 本研究发现农业观光活动需要互助合作, 例如自己动手作、动物互动喂食, 以及采摘蔬果等活动, 都会提升游客的再游意愿。更进一步的, 农业观光族群分为与孩童同行及未与孩童同行二类时, 动物喂食互动活动对其再游意愿的影响并不相同。更特别的是, 本研究发现游客与孩童同行时, 其再游意愿会受到动物喂食互动的影响；但是, 游客并未与孩童同行时则不会。

本研究证实了并非所有的农业观光活动都能提升再游意图。为此, 农业观光企业应考虑重新设计其游客与动物互动的观光活动, 例如增加对动物福祉的责任心, 特别是虐待动物的问题。另外, 关注在教育及生态的农业观光活动在先前区分的不同族群里都不受到青睐。

本研究发现显示了假若农业观光类型必须符合游客的预期及渴望, 游客才能感到满意的体验。作者认为游客对参与的某些观光活动之预想是一种不切实际的想像, 而这类想像是来自游客先前的经验及文化。因此, 作者综述关注植物及生态类的农业观光活动并不能达到人际间互动的目的。

Agroturismo: diseño de experiencia, actividades e intención de volver a visitor

Estudios anteriores han tratado los efectos individuales que tienen algunas actividades agroturísticas sobre la respuesta del visitante ignorando los efectos de interacción. Por eso, el objetivo de este estudio es tratar conjuntamente los efectos individuales y de interacción de las actividades agroturísticas sobre la intención de volver a visitar del turista.

Este estudio clasificó las actividades agroturísticas en cuatro categorías y recopiló 883 muestras válidas. A continuación, se aplicó la regresión logística para poner a prueba la influencia de las actividades agroturísticas sobre la intención de volver a visitar del turista.

Sobre la base de los resultados del análisis de estadística, se mostró que las actividades agroturísticas que requieren cooperación mutua, como el bricolaje, la interacción con animales o nutrición de ellos, así como la recogida de frutas y verduras aumentaron la intención de volver a visitar del turista. Asimismo, los grupos de agroturismo que participaron en actividades con o sin niños no tienen intenciones de volver a visitar consistentes a propósito de las actividades que implican interacción con animales o nutrición de ellos. En particular, este estudio desveló que la voluntad de volver para los turistas con niños está influenciada por las interacciones con animales o nutrición de ellos, mas no para los turistas sin niños.

Esta investigación demuestra que no todas las actividades agroturísticas fomentan la intención de volver a visitar. Por esta razón, las empresas de agroturismo deberían considerar volver a diseñar sus actividades en relación al visitante e interacciones con animales con escrupulosidad acerca del bienestar animal, especialmente con respeto al abuso animal. Además, estas actividades con enfoque sobre la educación y la ecología no son tan apreciadas por los turistas como muchos han ido asumiendo desde diferentes grupos.

Los resultados de este estudio muestran que si los tipos de actividades agroturísticas consiguen llenar las expectativas y los deseos de los visitantes, son mucho más propensos a tener una experiencia satisfactoria. Consideramos ciertas de estas nociones como fantasías poco realistas por lo que se refiere al agroturismo y al tipo de actividades implicadas en aquel. Este tipo de fantasías está probablemente formado por las experiencias pasadas y la cultura de los visitantes. Como resultado, concluimos que las actividades agroturísticas con foco en la educación sobre plantas y ecología no consiguen el verdadero objetivo preferido que es una mejor interacción con la gente.

The purpose of the study is to propose a normative approach for market segmentation, profile and monitoring using computing and information technology to analyze User-Generated Content (UGC).

The specific steps include performing a structural analysis of the UGC and extracting the base variables and values from it, generating a consumer characteristics matrix for segmenting process, and finally describing the segments' preferences, regional and dynamic characteristics. The authors verify the feasibility of the method with publicly available data. The external validity of the method is also tested through questionnaires and product regional sales data.

The authors apply the proposed methodology to analyze 53,526 UGCs in the New Energy Vehicle (NEV) market and classify consumers into four segments: Brand-Value Suitors (32%), Rational Consumers (21%), High-Quality Fanciers (26%) and Utility-driven Consumers (21%). The authors describe four segments' preferences, dynamic changes over the past six years and regional characteristics among China's top five sales cities. Then, the authors verify the external validity of the methodology through a questionnaire survey and actual NEV sales in China.

The proposed method enables companies to utilize computing and information technology to understand the market structure and grasp the dynamic trends of market segments, which assists them in developing R&D and marketing plans.

This study contributes to the research on UGC-based universal market segmentation methods. In addition, the proposed UGC structural analysis algorithm implements a more fine-grained data analysis.

Employees play an essential role in interactive innovation activities in Open Innovation Communities (OICs). Nevertheless, the factors influencing employees' innovation behavior in OICs have not been studied in depth. This study selects personality traits and social network characteristics to explain why and how these two factors affect employees' innovation behavior in OICs.

Three regression models were constructed to test the relationship between personality traits, social network characteristics, and interactive innovation behaviors. The authors examined how employees' personality traits (Big Five personality traits) influence employees' innovative behavior (initiating and supporting innovation) directly in OICs and explored whether social network characteristics (social group) mediate the relationship between employees' personality traits and employees' innovation behavior.

Using empirical data on 162 employees from Salesforce's IdeaExchange, the authors found that extraversion and openness to experience have significant positive effects on employees' interactive innovation behaviors, while conscientiousness has a significant negative effect on employees' interactive innovation behaviors in OICs. Furthermore, the mediation effect test results indicated that social network characteristics have a mediating effect on the relationship between extraversion and innovative behavior, and between openness and innovative behavior.

This study analyzes how personality traits influence innovation behavior in an open innovation environment, thus enriching research related to the factors influencing interactive innovation behavior. Meanwhile, the study integrates personality, social network, and innovative behavior research streams and clearly explains the relationship between the three variables. The research findings assist firms in selecting suitable employees to participate in interactive innovation behaviors in OICs.

With the rapid development and stable operated application of lithium-ion batteries used in uninterruptible power supply (UPS), the prediction of remaining useful life (RUL) for lithium-ion battery played an important role. More and more researchers paid more attentions on the reliability and safety for lithium-ion batteries based on prediction of RUL. The purpose of this paper is to predict the life of lithium-ion battery based on auto regression and particle filter method.

In this paper, a simple and effective RUL prediction method based on the combination method of auto-regression (AR) time-series model and particle filter (PF) was proposed for lithium-ion battery. The proposed method deformed the double-exponential empirical degradation model and reduced the number of parameters for such model to improve the efficiency of training. By using the PF algorithm to track the process of lithium-ion battery capacity decline and modified observations of the state space equations, the proposed PF + AR model fully considered the declined process of batteries to meet more accurate prediction of RUL.

Experiments on CALCE dataset have fully compared the conventional PF algorithm and the AR + PF algorithm both on original exponential empirical degradation model and the deformed double-exponential one. Experimental results have shown that the proposed PF + AR method improved the prediction accuracy, decreases the error rate and reduces the uncertainty ranges of RUL, which was more suitable for the deformed double-exponential empirical degradation model.

In the running of UPS device based on lithium-ion battery, the proposed AR + PF combination algorithm will quickly, accurately and robustly predict the RUL of lithium-ion batteries, which had a strong application value in the stable operation of laboratory and other application scenarios.

The objective of this study is to investigate the impact of geographical labeling (GL) and place of origin on consumers' perceived tea quality and purchase intention, as well as to analyze the moderating effects of traditional tea processing methods and the price of tea.

This study conducts two experiments by combining a simulated scenario with a questionnaire; overall, 383 and 678 valid samples were collected, respectively.

(1) The existence of GL is extremely important and will give consumers the perception of higher tea quality resulting in higher purchase intention. The tea’s production method and geographic location are strongly correlated. Thus, whether the tea is produced with traditional methods has a moderating effect on the place of origin, GL, and consumer response in study 1. (3) Different tea pricing has a moderating effect on the place of origin/GL and consumer response in study 2.

This study demonstrates the relationship between consumers' perception of tea GL, and their response helps to identify the difference between Eastern and Western tea culture, which can be used to help promote and market tea leaves. Multiple clues show a complementary effect between the place of origin and the GL on tea packaging. In addition, perception of the tea craftsmanship from the place of origin (long-term) and the price manipulation (short-term) have a moderating effect, which can be used to improve tea marketing design in academia and in practice.

The purpose of this paper is to explore maintenance strategies for manufacturing equipment in Chinese firms.

Data were collected from Chinese companies using a questionnaire administered during face‐to‐face interviews and two established methodologies in strategic management research, exploratory factor analysis and cluster analysis, were used to analyze the data.

The results suggest that despite increasing competitive capabilities of Chinese firms, their maintenance strategies are often restricted to corrective maintenance. Only very few Chinese firms have already implemented predictive maintenance approach, total productive maintenance programs or the strategic outsourcing of maintenance activities.

The research limitations stem from typical issues related to the use of exploratory factor analysis and cluster analysis (for example reliance on the subjective judgment of the researcher or the provision of clusters although no meaningful groups are embedded in the sample).

The findings highlight potential strategies for Chinese firms to improve their maintenance management.

This paper deals with a neglected area of operations management by exploring the maintenance approaches in fast growing Chinese manufacturing industries.

Cultural differences have been frequently cited as a major source of risks for international joint ventures (IJVs). Cultural differences may cause extensive conflicts in technology, norms and emotion among the international joint venture (IJV) partners. The purpose of this study is to explore the interactive effects of national culture differences (NCDs) and conflict management approaches on the performance of international construction joint ventures (ICJV).

Data were collected using a questionnaire survey method with 143 valid responses. Partial least squares structural equation modeling (PLS-SEM) was used to test the research hypotheses.

It was found that ICJV performance declined with a high degree of NCDs. The negative effect of NCDs on ICJV performance was mitigated by adopting the cooperative conflict management approach; while it was aggravated by adopting the competitive conflict management approach. The findings may provide an alternative way (i.e. adopting the cooperative conflict management approach rather than avoiding or competitive approaches) to address the cultural conflicts in the multicultural project management teams.

Firstly, as NCD negatively impacts performance of ICJVs, project managers should pay attention to cultural issues and learn how to manage them; Secondly, as cooperative and competitive conflict management approaches have different moderating effects on the relationship between NCD and ICJV performance, project managers must choose appropriate conflict management styles in multination teams. Thirdly, as the avoiding approach has no significant moderating effect on the negative relationship between NCD and ICJV performance, it is important for Chinese partners not to employ avoiding approach to deal with conflicts in ICJV.

This study uniquely adds to the literature on cultural issues in managing ICJVs by integrating the moderating effects of conflict management approaches. The interactive effects of conflict management approaches and national cultural differences on ICJV project performance may contribute to the theories regarding conflict management theory in the context of cross-cultural management.