Identifying customer behavioral factors and price premiums of green building purchasing

Juan, Yi‐Kai; Hsu, Yin-Hao; Xie, Xiaoyan

doi:10.1016/j.indmarman.2017.03.004

Cited by 47 publications

(17 citation statements)

References 39 publications

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“…Only a few researchers focused on the utility value of green buildings including two aspects, namely the green building's properties and consumers' features. Generally, transportation [35], the natural environment [36], and the humanity environment [37] are important contributors to a green building's value. As for the aspect of consumers' features regarding their views toward green buildings, salary and family life-cycle stage were two critical factors [38].…”

Section: Green Residential Building Valuementioning

confidence: 99%

Proposing a Value Field Model for Predicting Homebuyers’ Purchasing Behavior of Green Residential Buildings: A Case Study in China

Yuan

2019

Sustainability

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Understanding the motivations that stimulate homebuyers’ green purchasing behavior can increase market demand for green products, especially considering the comparably low market share of green products worldwide. In this context, various studies have been conducted examining consumers’ intentions to pay for green products. Nevertheless, there is still limited research on evaluating homebuyers’ purchasing behavior toward green residential buildings. This study argues that the value of green residential buildings (GRBs) affects their adoption, and thus exerts an invisible force on homebuyers’ purchasing behavior. It also finds that field theory provides a scientific perspective on this phenomenon. Thus, this paper proposes a value field model for evaluating homebuyers’ GRB purchasing behavior based on physical field theory and psychology field theory. In particular, physical field theory provides the measurement formula, while psychological field theory explains the effect of the force stimulating homebuyers’ purchasing intention, and ultimately influencing their purchasing behavior. The initial model consisted of a field source (green perceived value), target charge (GRB demand), distance (psychological distance), and value field factor. As the value field factor was calculated to be approximately equal to 1, the final model is a composite of a field source (green perceived value), target charge (GRB demand), and distance (psychological distance). The results validate the construction of the value field model on the basis of field theory. This research contributes to the body of knowledge by analyzing GRB value and provides a clearer understanding of how GRBs and the environment combine to fulfill homebuyers’ requirements and influence their GRB purchasing behavior.

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Section: Green Residential Building Valuementioning

confidence: 99%

Proposing a Value Field Model for Predicting Homebuyers’ Purchasing Behavior of Green Residential Buildings: A Case Study in China

Yuan

2019

Sustainability

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“…Forum dunia melalui International Organization of Consumers Unions (IOCU) atau yang sekarang dikenal dengan Consumers International (CI) mulai mengadopsi sebuah resolusi baru yang disebut dengan 'green consumerism' (Juan, Hsu, & Xie, 2017). Masyarakat mulai menyadari sebuah nilai dari perpaduan antara kepedulian alam dengan pelestarian budaya, konsep kesadaran ekologi dan green consumption menjadi sebuah revolusi terkini bagi para perusahaan dalam menciptakan dan membuat barang atau jasa.…”

Section: A Pendahuluanunclassified

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Prameka¹,

Kurniawan²

2021

istiqro

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Perusahaan mulai memberi perhatian lebih untuk masalah lingkungan dan menyesuaikan strategi green marketing agar mereka dapat menerapkan sebuah kebijakan baru. Penelitian ini dilakukan pada konsumen gerai kopi terkenal di Indonesia yang mengedepankan konsep "green marketing" dan menerapkan green concept pada pengoperasian manajerial yaitu Starbucks dan Fore Kopi. Tujuan penelitian ini adalah membangun konseptual model untuk mendeskripsikan secara empiris dan mengkonfirmasi repurchase intention melalui pendekatan green marketing. Sampel pada penelitian ini sebanyak 208 responden, dengan metode pengumpulan data melalui kuesioner. Teknik analisis regresi linier berganda digunakan dalam penelitian ini. Hasil penelitian menunjukkan bahwa seluruh variable green marketing mix berpengaruh positif terhadap repurchase intention, ini menunjukkan bahwa konsumen memiliki ketertarikan melakukan pembelian berulang dikarenakan oleh factor pendekatan green marketing yang dilakukan oleh perusahaan.

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“…Fortunately, automated procedures for gathering unstructured data are becoming more accessible. For example, supervised machine learning methods such as artificial neural networks (Juan, Hsu, & Xie, 2017;Timoshenko & Hauser, 2019), k-Nearest Neighbors (Dzyabura, Jagabathula, & Muller, 2019), naive Bayes (Hartmann et al, 2019), and random forests (Hoornaert, Ballings, Malthouse, & Van den Poel, 2017) inductively classify textual input based on observed patterns without the requirement of manually coded rules from the researcher (Dumais, Platt, Heckerman, & Sahami, 1998). Image classification approaches that have recently made their way into marketer's toolboxes include the use of openly available computer vision packages such as Google's Cloud Vision API, Microsoft's Computer Vision API, OpenCV, Amazon's Rekognition, and IBM's Watson Visual Recognition (Mazloom, Rietveld, Rudinac, Worring, & Van Dolen, 2016).…”

Section: Gather and Sourcementioning

confidence: 99%

Marketing ecosystem: An outside-in view for sustainable advantage

Zhang

Watson

2020

Industrial Marketing Management

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In the modern business environment, consumers are increasingly influenced by megatrends involving marketplace, technology, socioeconomics, geopolitics, and natural environment. Simultaneously, the data and insights that can inform consumer attitudes and behaviors often reside outside of firms' direct control. Consciously incorporating these interdependent factors into firms' decision-making is essential for adaptability and sustainable profitability. Building on the "outside-in" perspective, we propose that firm strategies should be informed through the lens of the marketing ecosystem that considers the interrelated and dynamic megatrends. By leveraging advances in data and technology, firms can sense-make the marketplace by extracting insights from massive amounts of diverse consumer data with modern-day analytics. By mapping out the megatrends with marketing analytics, firms can 1) more accurately predict consumers' changing preferences and formulate appropriate strategies to engage with them; and 2) become more market-adaptable and competitive in the present and the future. To deliver sustainably compelling value to customers, firms should adopt an ecosystem mindset and cooperate with various stakeholders. A broad-thinking, agile, and humble firm culture can enable the development of more robust outside-in capabilities. We elaborate on the megatrends in the interconnected world of the marketing ecosystem, and propose emerging research directions in each area.

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Identifying customer behavioral factors and price premiums of green building purchasing

Cited by 47 publications

References 39 publications

Proposing a Value Field Model for Predicting Homebuyers’ Purchasing Behavior of Green Residential Buildings: A Case Study in China

Proposing a Value Field Model for Predicting Homebuyers’ Purchasing Behavior of Green Residential Buildings: A Case Study in China

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Marketing ecosystem: An outside-in view for sustainable advantage

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