Exploring the dynamic influences and interaction effects of signals on backers’ investment in the crowdfunding market

2019 ◽  
Vol 33 (2) ◽  
pp. 792-812 ◽  
Author(s):  
Yang Song ◽  
Hong Wu ◽  
Jingdong Ma ◽  
Naiji Lu
Keyword(s):  
Panel Data ◽  
Negative Binomial ◽  
Early Stage ◽  
Substitution Effect ◽  
Interaction Effects ◽  
Data Set ◽  
Content Type ◽  
Funding Cycle ◽  
Practical Implications ◽  
Shed Light

Purpose As a standard source of capital for entrepreneurs, crowdfunding has recently gained wide attention in business and academia. With scientific endorsement, some research is conducted to explore the antecedents of online crowdfunding success. The factors that can influence the backers’ investment which is the key to success are information from prior backers’ and creators’ behaviors. Based on the signaling theory, the purpose of this paper is to systematically investigate the dynamic influences and interaction effects of signals with different forms (action-based or opinion-based signals) and sources (creator-sourced or backer-sourced signals) on backers’ investment behaviors over a project-funding cycle. Design/methodology/approach A panel data set of 3,010 projects with 640,625 transaction records from April 28, 2013 to September 31, 2017 is collected from a famous online crowdfunding platform – Zhongchou.cn in China and the negative binomial panel data model with fixed effect is used to obtain our empirical results. Findings The findings demonstrate that the work of different signals is significantly effective at the early stage of a project and decreases with time. Furthermore, our results show that there are both synergistic effect and substitution effect among different signals. Specifically, the direction of interaction effect depends on the forms of signals and the backers’ sensitivity toward that signal, and the interaction effects are also dynamic. Originality/value This paper has shed light on the roles of different signal types and their interactions in influencing funding behavior over a project-funding cycle, enriched the literature on crowdfunding and provided both theoretical and practical implications.

Fusion based learning approach for predicting concrete pouring productivity based on construction and supply parameters

2016 ◽  
Vol 16 (2) ◽  
pp. 185-202 ◽  
Author(s):  
Mojtaba Maghrebi ◽  
Ali Shamsoddini ◽  
S. Travis Waller
Keyword(s):  
Supply Chain ◽  
Production Rate ◽  
Learning Method ◽  
Data Set ◽  
Content Type ◽  
Field Database ◽  
The Stability ◽  
Stable Learning ◽  
Ready Mixed Concrete ◽  
Practical Implications

Purpose The purpose of this paper is to predict the concrete pouring production rate by considering both construction and supply parameters, and by using a more stable learning method. Design/methodology/approach Unlike similar approaches, this paper considers not only construction site parameters, but also supply chain parameters. Machine learner fusion-regression (MLF-R) is used to predict the production rate of concrete pouring tasks. Findings MLF-R is used on a field database including 2,600 deliveries to 507 different locations. The proposed data set and the results are compared with ANN-Gaussian, ANN-Sigmoid and Adaboost.R2 (ANN-Gaussian). The results show better performance of MLF-R obtaining the least root mean square error (RMSE) compared with other methods. Moreover, the RMSEs derived from the predictions by MLF-R in some trials had the least standard deviation, indicating the stability of this approach among similar used approaches. Practical implications The size of the database used in this study is much larger than the size of databases used in previous studies. It helps authors draw their conclusions more confidently and introduce more generalised models that can be used in the ready-mixed concrete industry. Originality/value Introducing a more stable learning method for predicting the concrete pouring production rate helps not only construction parameters, but also traffic and supply chain parameters.

scholarly journals A surrogate-based generic classifier for Chinese TV series reviews

2017 ◽  
Vol 45 (2) ◽  
pp. 66-74
Author(s):  
Yufeng Ma ◽  
Long Xia ◽  
Wenqi Shen ◽  
Mi Zhou ◽  
Weiguo Fan
Keyword(s):  
Design Methodology ◽  
Experimental Result ◽  
Digital Information ◽  
Data Set ◽  
Content Type ◽  
Category Labels ◽  
Information Supply Chain ◽  
Feature Selection Techniques ◽  
Practical Implications

Purpose The purpose of this paper is automatic classification of TV series reviews based on generic categories. Design/methodology/approach What the authors mainly applied is using surrogate instead of specific roles or actors’ name in reviews to make reviews more generic. Besides, feature selection techniques and different kinds of classifiers are incorporated. Findings With roles’ and actors’ names replaced by generic tags, the experimental result showed that it can generalize well to agnostic TV series as compared with reviews keeping the original names. Research limitations/implications The model presented in this paper must be built on top of an already existed knowledge base like Baidu Encyclopedia. Such database takes lots of work. Practical implications Like in digital information supply chain, if reviews are part of the information to be transported or exchanged, then the model presented in this paper can help automatically identify individual review according to different requirements and help the information sharing. Originality/value One originality is that the authors proposed the surrogate-based approach to make reviews more generic. Besides, they also built a review data set of hot Chinese TV series, which includes eight generic category labels for each review.

Exploring innovation creation across rural and urban firms

2018 ◽  
Vol 7 (4) ◽  
pp. 357-376 ◽  
Author(s):  
Giri Aryal ◽  
John Mann ◽  
Scott Loveridge ◽  
Satish Joshi
Keyword(s):  
National Survey ◽  
Negative Binomial ◽  
Secondary Data ◽  
Firm Level ◽  
Data Set ◽  
Content Type ◽  
Rural And Urban ◽  
Wide Range ◽  
Rural Firms ◽  
Urban Firms

Purpose The innovation creation literature primarily focuses on urban firms/regions or relies heavily on these data; less studied are rural firms and areas in this regard. The purpose of this paper is to employ a new firm-level data set, national in scale, and analyze characteristics that potentially influence innovation creation across rural and urban firms. Design/methodology/approach The authors use the 2014 National Survey of Business Competitiveness (NSBC) covering multiple firm-level variables related to innovation creation combined with secondary data reflecting the regional business and innovative environments where these firms operate. The number of patent applications filed by these firms measures their innovation creation, and the paper employs a negative binomial regression estimation for analysis. Findings After controlling for industry, county and state factors, rural and urban firms differ in their innovation creation characteristics and behaviors, suggesting that urban firms capitalize on their resources better than rural firms. Other major findings of the paper provide evidence that: first, for rural firms, the influence of university R&D is relevant to innovation creation, but their perception of university-provided information is not significant; and second, rural firms that are willing to try, but fail, in terms of innovation creation have a slight advantage over other rural firms less willing to take on the risk. Originality/value This paper is one of the first to analyze the 2014 NSBC, a firm-level national survey covering a wide range of innovation-related variables. The authors combine it with other regional secondary data, and use appropriate analytical modeling to provide empirical evidence of influencing factors on innovation creation across rural and urban firms.

The effect of industry association on firm innovation in Chinese private ventures

2019 ◽  
Vol 57 (9) ◽  
pp. 2414-2435
Author(s):  
Wenge Zhang ◽  
Jun Li ◽  
Yiyuan Mai
Keyword(s):  
Moderating Effects ◽  
Firm Level ◽  
Firm Innovation ◽  
Data Set ◽  
Industry Association ◽  
Content Type ◽  
Emerging Industries ◽  
Practical Implications ◽  
Firm Learning

Purpose The purpose of this paper is to examine the relationship between industry association membership and firm innovation in Chinese private ventures. A secondary objective is to investigate potential moderating effects of firm learning practices and founder characteristics on the above relationship, and to draw out implications for policymakers and practitioners. Design/methodology/approach The paper utilizes data from a sample of 567 Chinese entrepreneurial firms operating in 9 designated emerging industries. Hierarchical regression models were employed to analyze the effect of industry association membership on firm innovation, and the potential moderating effects. A 2SLS procedure was adopted to control for potential endogeneity issue. Supplemental analyses were conducted to ensure the robustness of the findings. Findings The paper provides empirical insights about how industry association membership, along with firm learning practice and founder leadership, affect firm innovation in Chinese private ventures in emerging industries. It suggests that industry association membership positively affects firm innovation. Further, there is a three-way interaction effect of industry association membership, learning practice and founder power on innovation. Research limitations/implications Due to the design of the data set, there are some limitations. First, the study only considered whether a firm belongs to an industry association, but not the nature of such membership (length, firm status in the association, etc.). Second, the cross-sectional design may limit the power of the study to make casual implications about the tested relationships. Practical implications The paper provides important practical implications for policymakers and entrepreneurs in China. In general, the results suggest that private ventures pursuing innovation in emerging industries can benefit from industry associations, and entrepreneurs shall actively engage in firm-level and personal-level learning. For policymakers, the study suggests that to foster innovation in an emerging industry, special attention shall be paid to building necessary institutional support to develop and to strengthen the role of industry association in the industry. Originality/value This paper fulfills an important gap in the literature in that it is one of the first, which investigates the role of the industry association in firm innovation, especially in a non-western context. This paper provides new insights into the role of industry association and firm innovation in an under-researched developing economy context.

Kit preparation for mixed-model assembly: efficiency impact of confirmation methods

2019 ◽  
Vol 119 (3) ◽  
pp. 547-560 ◽  
Author(s):  
Patrik Fager
Keyword(s):  
Learning Curve ◽  
Design Methodology ◽  
Mixed Model ◽  
Early Stage ◽  
Time Efficiency ◽  
Content Type ◽  
Order Batching ◽  
The Impact ◽  
Mixed Model Assembly ◽  
Practical Implications

PurposeConfirmations are applied in kit preparation for mixed-model assembly to promote quality, but research that explains the impact on time efficiency has been lacking. The purpose of this paper is to determine the extent to which the type of confirmation method relates to time-efficient kit preparation when order batching is applied.Design/methodology/approachAn industrially relevant laboratory experiment is applied, simulating kit preparation with order batching for mixed-model assembly. The time efficiency is studied as associated with four confirmation methods – barcode ring scanner, button presses, voice commands and RFID-reading wristbands – when applied as pick-from and place-to confirmation. Furthermore, the paper also considers the quality outcome.FindingsEfficiency is promoted by methods that minimise interrupting the picker’s motions when performing pick-from confirmations and with methods that allow each hand to place components and perform place-to confirmations simultaneously – here represented by button presses and RFID-reading wristbands. Moreover, combining various methods for the tasks of pick-from or place-to confirmation can benefit efficiency.Research limitations/implicationsPickers at an early stage of the learning curve (one shift of training) were considered.Practical implicationsThe findings promote the customised applications of picking information systems in industry.Social implicationsCombining various methods for the tasks of pick-from and place-to confirmation can provide more fitting applications that better align with the picker’s preferences.Originality/valueCombinations of various methods when applied as either pick-from or place-to confirmation, or both, are studied.

Modeling debt choice in agriculture: the effect of endogenous asset values

2017 ◽  
Vol 77 (1) ◽  
pp. 95-110 ◽  
Author(s):  
Maria Bampasidou ◽  
Ashok K. Mishra ◽  
Charles B. Moss
Keyword(s):  
Panel Data ◽  
Interest Rate ◽  
Agricultural Sector ◽  
Macroeconomic Policy ◽  
Rate Of Return ◽  
Data Set ◽  
Content Type ◽  
Asset Values ◽  
The Usa ◽  
Non Parametric

Purpose The purpose of this paper is to investigate the endogeneity of asset values and how it relates to farm financial stress in US agriculture. The authors conceptualize an implied measure of farm financial stress as a function of debt position. The authors posit that there are variations in the asset values that are beyond the farmer’s control and therefore have implications on farm debt. Design/methodology/approach The framework recognizes the endogeneity of return on assets (ROA). It uses a non-parametric technique to approximate the variance of expected ROA (VEROA). The authors model the rate of return on agricultural assets and interest rate with a formulation that focuses on macroeconomic policy. Further, the authors use a dynamic balanced panel data set from 1960 to 2011 for 15 US agricultural states from the Agricultural Resource Management Survey, and information from traditional state-level financial statements. Findings Estimation of linear dynamic debt panel data models accounting for the endogeneity of ROA and VEROA is a challenging task. Estimated variances are unstable. Hence, the authors focus on variance specification that uses the residuals squared from the ARIMA specification and non-parametric estimators. Arellano-Bover/Blundell-Bond generalized method of moments estimation procedures, although may be biased, show that VEROA has a negative and significant effect on the total amount of debt in the agricultural sector. Research limitations/implications The instruments used in this analysis are lagged regressors which may be weakly correlated with the relevant first-order condition, hence not properly identifying the parameters of interest. Future research could include the identification of better instruments, potentially use of sequential moment conditions. Originality/value Unlike previous study, the authors use non-parametric approximation of VEROA. The authors model the rate of return on agricultural assets and interest rate with a formulation that focuses on macroeconomic policy. Second, the authors make use of a large dynamic balanced panel data set from 1960 to 2011 for 15 agricultural states in the USA. To the best of the authors’ knowledge, this study is one of the few that provides evidence on risk-balancing behavior at the agricultural sector level, of the USA.

Students' perceptions of education for sustainable development

2014 ◽  
Vol 15 (2) ◽  
pp. 242-253 ◽  
Author(s):  
Yvonne Zeegers ◽  
Ian Francis Clark
Keyword(s):  
Design Methodology ◽  
Pedagogical Approach ◽  
Data Set ◽  
Content Type ◽  
Tertiary Institutions ◽  
Reflective Journal ◽  
Reflective Journals ◽  
The Social ◽  
Perceptions Of Education ◽  
Practical Implications

Purpose – This study investigated whether a course which focused on raising students' awareness of sustainability, from a balanced perspective, that is, one which gives equal consideration to the social and economic aspects as well as the environmental would produce graduates with the knowledge and commitment required to drive the sustainability agenda forward. The paper aims to discuss these issues. Design/methodology/approach – An analysis of students' final entries in their reflective journal was used to explore whether their views on sustainability reflected a balanced view. Findings – The findings of this research confirmed previous studies showed that initially students do have an enviro-centric bias. It also showed that despite experiencing a pedagogical approach which challenged views by encouraging discussion, debate, and reflection and which provided what was considered to be a balanced view of sustainability, many of the students still leaned towards an environmentally focused perspective of sustainability. Research limitations/implications – The conclusions are based on one data set but are supported by other data described in the paper. Practical implications – The finding led the authors to conclude that a concerted holistic effort within and across courses is needed within tertiary institutions if students' views about sustainability are to be challenged. Originality/value – The outcomes demonstrate that students' reflective journals can be used to gather information about the change in students' perceptions about sustainability.

Creating space and time for innovation - a methodology for building adaptation design appraisal using physics-based simulation tools and interactive multi-objective optimization

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sheida Shahi ◽  
Philip Beesley ◽  
Carl Thomas Haas
Keyword(s):  
Decision Making ◽  
Early Stage ◽  
Design Decision ◽  
Stage Design ◽  
Content Type ◽  
Simulation Tools ◽  
Building Adaptation ◽  
Early Stage Design ◽  
Physics Based Simulation ◽  
Practical Implications

PurposeIt is crucial to consider the multitude of possible building adaptation design strategies for improving the existing conditions of building stock as an alternative to demolition.Design/methodology/approachIntegration of physics-based simulation tools and decision-making tools such as Multi-Attribute Utility (MAU) and Interactive Multi-objective Optimization (IMO) in the design process enable optimized design decision-making for high-performing buildings. A methodology is presented for improving building adaptation design decision making, specifically in the early-stage design feasibility analysis. Ten residential building adaptation strategies are selected and applied to one primary building system for eight performance metrics using physics-based simulation tools. These measures include energy use, thermal comfort, daylighting, natural ventilation, systems performance, life cycle, cost-benefit and constructability. The results are processed using MAU and IMO analysis and are validated through sensitivity analysis by testing one design strategy on three building systems.FindingsQuantifiable comparison of building adaptation strategies based on multiple metrics derived from physics-based simulations can assist in the evaluation of overall environmental performance and economic feasibility for building adaptation projects.Research limitations/implicationsThe current methodology presented is limited to the analysis of one decision-maker at a time. It can be improved to include multiple decision-makers and capture varying perspectives to reflect common practices in the industry.Practical implicationsThe methodology presented supports affordable generation and analysis of a large number of design options for early-stage design optimization.Originality/valueGiven the practical implications, more space and time is created for exploration and innovation, resulting in potential for improved benefits.

The impact of ownership structure on corporate tax avoidance with corporate social responsibility as mediating variable

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anissa Dakhli
Keyword(s):  
Corporate Social Responsibility ◽  
Social Responsibility ◽  
Tax Avoidance ◽  
Institutional Ownership ◽  
Corporate Tax ◽  
Data Set ◽  
Content Type ◽  
Corporate Social ◽  
The Impact ◽  
Practical Implications

Purpose The purpose of this paper is to investigate the direct and indirect relationship between institutional ownership and corporate tax avoidance using corporate social responsibility (CSR) as a mediating variable. Design/methodology/approach This study uses panel data set of 200 French firms listed during the 2007–2018 period. The direct and indirect effects between managerial ownership and tax avoidance were tested by using structural equation model analysis. Findings The results indicate that institutional ownership negatively affects tax avoidance. The greater the proportion of the institutional ownership, the lower the likelihood of tax avoidance usage. From the result of the Sobel test, this study indicated that CSR partially mediates the effect of institutional ownership on corporate tax avoidance. Practical implications The findings have some policy and practical implications that may help regulators in improving the quality of transactions and in achieving more efficient market supervision. They recommend to the government to add regulations and restrictions to the structure of corporate ownership to control corporate tax avoidance in French companies. Originality/value This study extends the existing literature by examining both the direct and indirect effect of institutional ownership on corporate tax avoidance in French companies by including CSR as a mediating variable.

Too tied to fail: a multidimensional approach to social capital in crowdfunding campaigns. Evidences from Italian agri-food businesses

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ulpiana Kocollari ◽  
Alessia Pedrazzoli ◽  
Maddalena Cavicchioli ◽  
Andrea Girardi
Keyword(s):  
Social Capital ◽  
Design Methodology ◽  
Multidimensional Approach ◽  
Data Set ◽  
Content Type ◽  
Different Types ◽  
Linear Regressions ◽  
Practical Implications

PurposeThe authors investigate the contributions of social capital (SC) dimensions (bridging, bonding and linking) in crowdfunding campaigns by comparing the dynamics of agri-food businesses with those of two other sectors – cultural and technological.Design/methodology/approachThe authors develop linear regressions on a proprietary data set of 5,290 projects launched on the Italian platform “Produzionidalbasso.com”, from 2014 to 2020.FindingsThe authors’ findings suggest that combining the three social capital dimensions (bridging, bonding and linking) has a more substantial overall effect on the number of backers involved in agri-food projects than in cultural and technological projects. Agri-food entrepreneurs effectively mobilize all resources embedded in the SC dimensions and therefore create the conditions to develop new ties that financially support the project.Practical implicationsAgri-food entrepreneurs may benefit from those results improving their funding strategies. Therefore, agri-food entrepreneurs can explore and exploit the instruments available on the CFD platform – video and rewards associated with the campaign – gaining more benefit from the backers involved compared with other project categories.Originality/valueThe study proposes a broader perspective regarding SC that encompasses the proponent, the company and the campaign with three different types of ties: bonding, bridging and linking. These SC dimensions can differently shape diverse sectors and this eclectic configuration can differentiate the effects of SC in crowdfunding campaigns. This study pinpoints how crowdfunding determinants change, based on project categories.

Sign in / Sign up

Export Citation Format

Share Document