Liya A, Qian Qin, Hafiz Waqas Kamran, Anusara Sawangchai, Worakamol Wisetsri and Mohsin Raza
This study purposes to measure the influencing relations between macroeconomic indicators and the prices of gold. Further study measures several factors with the gold price in the…
Abstract
Purpose
This study purposes to measure the influencing relations between macroeconomic indicators and the prices of gold. Further study measures several factors with the gold price in the context of the United States.
Design/methodology/approach
The secondary data are collected to measure relationship and fluctuation of gold prices the data collected from the website world development indicators (WDI) for the period of 31 years 1990–2019. This paper uses different econometric analysis such as analytical unit root test for stationary of data, descriptive statistical analysis for description of data, correlation coefficient test for measuring the inter correlation, and ordinary least square regression analysis for determine the impact of dependent and independents variables. In this research paper, gross domestic product (GDP), inflation rate (IR), unemployment rate (UR), real interest rate (RIR), gross national product (GNP), standard trade value (STV) are included in macroeconomic indicators and consider as independent. The gold prices are considered as dependent variable.
Findings
This study's overall results show an important and optimistic association between GDP, IR and STV with the gold price. Moreover, the RIR shows negative and does not show significant relation with the gold prices.
Originality/value
Since several economic crises were included during the data selection studied in this research paper, data error may be present, resulting in the instability of the overall data. However, the study still hopes to find the guiding role of these macro gold price factors in the price of gold from the limited data set. The basic scope of research is that research is limited in the United States.
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Liya Wang, Rong Cong, Shuxiang Wang, Sitan Li and Ya Wang
The research aims to explore the influence mechanism of peer feedback and users' knowledge contribution behavior. This study draws on the social identity theory and considers…
Abstract
Purpose
The research aims to explore the influence mechanism of peer feedback and users' knowledge contribution behavior. This study draws on the social identity theory and considers social identity as a mediating factor into the research framework.
Design/methodology/approach
This paper collected users' activity data of 142,191 ideas submitted by 76,647 users from the MIUI community between October 2010 and May 2018 via Python software, and data were processed using Stata 16.0.
Findings
The results indicate that knowledge feedback and social feedback positively influence users' knowledge contribution (quantity and quality), respectively. User's cognitive identity positively mediates the relationship between peer feedback and knowledge contribution behavior, affective identity positively mediates the relationship between peer feedback and knowledge contribution behavior, while evaluative identity positively mediates the relationship between peer feedback and knowledge contribution quality, but there is no mediating effect between peer feedback and knowledge contribution quantity.
Originality/value
This study advances knowledge management by highlighting peer feedback on online innovation communities. By demonstrating the significant mediating effect of social identity, this study empirically clarifies the relationships of peer feedback (knowledge feedback and social feedback) to specific dimensions of knowledge contribution, thereby providing managerial guidance to the online innovation community on incentivizing and managing user interaction to foster the innovation development of firms.
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Qian Zhou, Shuxiang Wang, Liya Wang and Wei Xu
Open innovation platform has become an effective field through which enterprises can acquire valuable knowledge for incremental and breakthrough innovation. However, as more…
Abstract
Purpose
Open innovation platform has become an effective field through which enterprises can acquire valuable knowledge for incremental and breakthrough innovation. However, as more entities join the innovation platform, the knowledge activities in the platform ecosystem are now facing higher complexity and vulnerability due to the differences in the knowledge demands as well as conflicting interest claims of participants. The lack of mature governance mechanisms has caused opportunistic behaviors like knowledge infringement, leakage and hiding, which seriously hinder the in-depth knowledge sharing and effective utilization. What’s more, the enthusiasm for collaborative innovation also reduced among multi-subjects. Therefore, the purpose of this study is to improve platform participants’ innovation ambidexterity under the guidance of scientific design of platform knowledge governance mechanisms through improved knowledge transformation processes.
Design/methodology/approach
Therefore, based on knowledge governance theory and knowledge transformation model (SECI, socialization-externalization-combination-internalization), the study explored the influence of relationship and contractual knowledge governance on the innovation ambidexterity of platform participants through the mediation effect of knowledge transformation. To better analyze complex causal relationships among variables and the chain multiple mediation effect, structural equation modeling is used, coupled with bootstrap analysis verification.
Findings
Platform contractual governance and relationship governance can positively influence the innovation ambidexterity of participants through knowledge trading and reuse, as well as through knowledge sharing and creation. The findings not only contribute to optimizing the effectiveness of knowledge activities on digital platforms but also provide empirical evidence and practical insights to support enterprises’ incremental and breakthrough innovation according to their own knowledge bases.
Practical implications
The findings offer valuable insights for providing decision-making guidance not only for platform-leading enterprises but also for individual and enterprise users on effectively using open innovation platforms to conduct knowledge seeking, trading or sharing and knowledge reuse or creation to enlarge the incremental innovation value and to trigger breakthrough innovation value in their product and technology developments.
Social implications
Through diverse knowledge governance mechanisms, platform-leading enterprises do not only act as “economic agents” with private attributes to reduce knowledge asymmetry in the public trading market, diffuse knowledge broadly and mitigate cooperation costs to increase economic value; they also serve as “social actors” for multilateral participants to increase the cohesion of knowledge sharing and creation to provide sustainable knowledge fuel for the higher level of breakthrough innovation. Overall, knowledge arrangement efficiency can be optimized, and breakthrough innovation value can be activated in a well-governed platform, gradually escaping the diminishing marginal benefits of exploitative innovation.
Originality/value
This study has extended the views of the knowledge transformation model under the platform context and proposed dualistic knowledge transformation pathways, named “tacit knowledge socialization” and “explicit knowledge combination,” respectively. Besides, it discovered that under the contractual and relationship knowledge governance mechanisms’ guiding, participants in open innovation platforms may choose different knowledge searching and exchange ways according to their knowledge needs and thus trigger the different knowledge transform process. Then, “tacit knowledge socialization” transformation can show larger positive impact on breakthrough innovation, while “explicit knowledge combination” transformation makes larger impact on incremental innovation.
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Nan Wang, Tian Lv, Liya Wang, Aifang Guo and Zhenzhong Ma
Online brand communities (OBCs) are important platforms to obtain consumers' ideas. The purpose of this study is to examine how peer influence and consumer contribution behavior…
Abstract
Purpose
Online brand communities (OBCs) are important platforms to obtain consumers' ideas. The purpose of this study is to examine how peer influence and consumer contribution behavior simulate innovative behaviors in OBCs to increase idea quality.
Design/methodology/approach
Using a firm-hosted popular online brand community – Xiaomi Community (MIUI), the authors collected a set of data from 6567 consumers and then used structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to empirically test the impact of peer influence and consumer contribution behaviors on idea quality in OBCs.
Findings
The results of this study show that both peer influence breadth and depth have a positive effect on idea adoption and peer recognition, wherein proactive contribution behavior positively mediates these relationships, and responsive contribution behavior negatively mediates the impact of peer influence breadth and peer influence depth on peer recognition. A more detailed analysis using the fsQCA method further identifies four types of antecedent configurations for better idea quality.
Originality/value
Based on the attention-based view and the theory of learning by feedback, this study explores the factors that affect idea quality in the context of social networks and extends the research of peer influence in the digital age. The paper helps improve our understanding of how to promote customer idea quality in OBCs.
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Estimating product cost at the design stage, often referred to as product costing, is vitally important in the product configuration process in the mass customization paradigm…
Abstract
Purpose
Estimating product cost at the design stage, often referred to as product costing, is vitally important in the product configuration process in the mass customization paradigm. There are three research streams in this field: analogous, statistical, and analytical methods. However, in a mass customization environment, these methods suffer the drawbacks of poor accuracy, low‐agility and an undesirable degree of detail. It is imperative to develop an efficient framework for product costing in mass customization. The paper aims to address these issues.
Design/methodology/approach
Activity‐based costing (ABC) becomes a new trend in product costing which alleviates the shortcomings discussed above. However, the complexity of ABC probably increases in mass customization with a high degree of variety. In this research, a framework is formalized for product costing in mass customization, in which a generic activity definition is proposed to simplify and catalyze ABC practice in high‐variety production. Moreover, an activity dictionary with a hierarchical structure is developed to bring commonality and modularity to the storage and retrieval of activity data.
Findings
A generic activity‐dictionary‐based method for product costing in mass customization is developed.
Research limitations/implications
The method proposed for product costing provides valuable cost data for product specifications, as well as the activities to create them. Therefore, a product configuration solution can be financially evaluated and optimized.
Practical implications
Based on the methodology proposed, a prototype system has been developed and implemented in a computer‐assembling company.
Originality/value
This paper alleviates the negative impact of activity variety on product costing.
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Shixiong Zhao, Liya Wang and Yu Zheng
Making decisions on production and maintenance separately, as is often done in practice and research literature, may not result in overall optimization. This paper aims to propose…
Abstract
Purpose
Making decisions on production and maintenance separately, as is often done in practice and research literature, may not result in overall optimization. This paper aims to propose a joint method that better integrates production planning and maintenance at the tactical level. The potential of improving the performance of the classic planning method is also explored.
Design/methodology/approach
An integrated production planning and maintenance model is proposed. The production capacity losses resulted from both preventive and corrective maintenance activities are considered. Meanwhile, the reliability deterioration of the machine is considered to be operation dependent. An iterative approach is presented to find a solution for the nonlinear model through iteratively solving a sequence of mixed integer linear programming instances, accompanied by modification of some parameters prior to each iteration. Computational experiments are conducted to evaluate the performance of the proposed method compared with three other methods, including two methods based on separate planning and one integrated model.
Findings
The superiority of the proposed method compared with all the other three methods is demonstrated. Thus, the values of both integrated planning and considering operation-dependent failures are testified. The advantage of the proposed method is highlighted in the cases of high capacity utilization, long maintenance durations and low maintenance costs. The performance of the two methods based on separate planning is sensitive to the system utilization, and when utilization is high, the one with an availability-sensitive objective function defined for the maintenance problem performs better.
Originality/value
Few studies have been carried out to integrate decisions on production lot and maintenance. Their considerations are either incomplete or not realistic enough. A more comprehensive and realistic integrated model is proposed in this paper, along with an iterative solution algorithm for it. A potential way to improve the performance of the classic planning method with its simplicity preserved is also presented.
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Mingxing Wu, Liya Wang, Ming Li and Huijun Long
This paper aims to propose a novel method to predict and alleviate feature fatigue. Many products now are loaded with an extensive number of features. Adding more features to one…
Abstract
Purpose
This paper aims to propose a novel method to predict and alleviate feature fatigue. Many products now are loaded with an extensive number of features. Adding more features to one product generally makes the product more attractive on the one hand but, on the other hand, may result in increasing difficulty to use the product. This phenomenon is called “feature fatigue”, which will lead to dissatisfaction and negative word-of-mouth (WOM). Feature fatigue will damage the brand’s long-term profit, and ultimately decrease the manufacturer’s customer equity. Thus, a problem of balancing the benefit of increasing “attractiveness” with the cost of decreasing “usability” exists.
Design/methodology/approach
A novel method based on the Bass model is proposed to predict and alleviate feature fatigue. Product capability, usability and WOM effects are integrated into the Bass model to predict the impacts of adding features on customer equity in product development, thus helping designers alleviate feature fatigue. A case study of mobile phone development based on survey data is presented to illustrate and validate the proposed method.
Findings
The results of the case study demonstrate that adding more features indeed increases initial sales; however, adding too many features ultimately decreases customer equity due to usability problems. There is an optimal feature combination a product should include to balance product capability with usability. The proposed method makes a trade-off between initial sales and long-term profits to maximize customer equity.
Originality/value
The proposed method can help designers predict the impacts of adding features on customer equity in the early stages of product development. It can provide decision supports for designers to decide what features should be added to maximize customer equity, thus alleviating feature fatigue.
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Zongshui Wang, Wei Liu, Zhuo Sun and Hong Zhao
Building on social media and destination brand-related literature, this study aims to explore World Heritage Sites’ (WHSs) brand diffusion and formation process from long-term and…
Abstract
Purpose
Building on social media and destination brand-related literature, this study aims to explore World Heritage Sites’ (WHSs) brand diffusion and formation process from long-term and short-term perspectives, which includes brand diffusion, user-generated content (UGC), opinion leaders and brand events’ impact.
Design/methodology/approach
This study uses a mixed-method including text mining, keyword analysis and social network analysis to explore the brand formation process of four popular WHSs in Beijing, namely, the Palace Museum, Great Wall, Summer Palace and Temple of Heaven and more than 10,000,000 users’ data on Sina Weibo has been implemented to uncover the underlying social media branding mechanism.
Findings
The results show that the number of postings keeps in a stable range in most months, but, in general, there are no common rules for changing trends among the four WHSs; long-term high-frequency keywords related to history and culture account for a higher percentage; different kinds of accounts have varying impacts on information diffusion, in which media accounts lead to a bigger influence. However, more followers do not necessarily mean more interactions and most of the interaction ratio is much lower than 0.01000; brand events facilitate brand dissemination and have an impact on the creation of UGC.
Practical implications
This study is valuable for destination marketers to deeper understand brand diffusion and formation and provides valuable insights for developing effective destination marketing strategies.
Originality/value
Unlike previous studies that only concern a few parts of destination brand formation via social media (e.g. brand diffusion, brand events or opinion leaders’ impact), this study takes a more comprehensive perspective by systematically analyzing the brand formation process of WHSs on social media. By considering both long-term diffusion and short-term representative events, this study provides a more holistic understanding of the branding mechanism.
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Karen Desta Agulei, John T. Githaiga, Benson Dulo and Eric Oyondi Nganyi
This study aims to identify the bioactive compounds in the Onion (Allium burdickii [A.B]) bulb using Raman and Fourier transform infrared spectroscopy (FTIR) spectroscopy. It…
Abstract
Purpose
This study aims to identify the bioactive compounds in the Onion (Allium burdickii [A.B]) bulb using Raman and Fourier transform infrared spectroscopy (FTIR) spectroscopy. It assessed the extraction conditions of bioactive compounds from A.B. while evaluating the best extraction conditions.
Design/methodology/approach
The research opted for an experimental qualitative approach. It examined the extraction conditions of A.B., namely, temperature (°C), time (min) and mass-to-liquor ratio (M:R) using ultraviolet-visible spectrophotometry. Identification of bioactive compounds present in the dye was performed using Raman spectroscopy and the validation of the results was done by FTIR spectroscopy.
Findings
The study determined the best extraction conditions (time, temperature, M:R) for A.B bulb. The study confirmed the presence of bioactive compounds.
Research limitations/implications
The limitation was quantification of bioactive compounds in A.B bulb.
Practical implications
The findings prove that the A.B. bulb can provide a sustainable source of bioactive compounds (functionalized compounds). The study provides suitable extraction conditions for A.B. and further elaborates on the techniques for identifying bioactive compounds in A.B. bulb extracts.
Social implications
The study provides A.B. as a source of bioactive compounds and a clean dye for textile coloration.
Originality/value
To the best of the authors’ knowledge, there is no documented study on the qualitative analysis of bioactive compounds in A.B using Raman and FTIR. Therefore, the study fulfils the identified need to ascertain alternative procedures for the analysis of bioactive compounds.