Cultural nuance, human behaviour and social identity require greater attention within the emerging smart city phenomenon. This special issue critically considers identity and urban culture as central to the smart city challenge. Current discourse on smart cities is obsessed with technological capability and development. Global rankings reduce cities to a one-dimensional business model and series of metrics. If the term ‘smart city’ is to have any enduring value, technology must be used to develop a city’s unique cultural identity and quality of life for the future. The editorial reviews emerging research on the cultural dimensions of urban innovation and smart cities and places the six special issue papers within a theoretical context. Each paper critiques smart city theories in relation to the practical challenge of enhancing urban identity, quality and value at a range of scales and geographic contexts. Three main themes are used to frame the debate on smart cities and urban innovation: 1) local development histories, 2) face-to-face relationships and 3) local community scales. Each of these themes is lacking in current smart city approaches and requires innovative approaches to integrate into the smart city of tomorrow.

Introduction

The world is experiencing a ῾smart city᾿ boom. New radical technologies have been integrated in smart cities to create an explosion of data flows that are described in today’s technical jargon as ῾big data᾿. In some ways, the term is disingenuous, as these data flows are so immense they are changing the face of the global economy (Kenney & Zysman, 2016). The most valuable resource in the world is ῾no longer oil, but data (The Economist, 2017)᾿. A new economy and networked business model have emerged to tap value from this growing asset. Cities are playing catch-up, learning how to negotiate big data and disruptive business models or platform capitalism by companies such as Alphabet (Google’s parent company), Apple, Amazon, Uber, Airbnb and Microsoft. The data economy is a major driver of urban change. Smart cities are seeking to process and manage the real-time data flowing from new digital infrastructure and services. Today’s citizens carry a complex package of sensors and devices in their pockets. This technology is networked within the smart city to form an informational footprint of startling complexity. Smart cities, by definition, refer to the data economy, stimulation from ICTs and improved urban management from software algorithms integrated within the urban fabric (Kitchin, 2014). As noted by Kitchin (2014), smart cities are ῾increasingly driven by technically inspired innovation, creativity and entrepreneurship᾿ (p. 131). However, a technocratic focus will not deliver the outcomes that are necessary to create more liveable cities that innovate across all areas of society, from the environmental to social and economic areas. First-generation smart cities have inspired research into digital technologies and their business potential. However, is this technologyand-business-based focus enough? Vanolo (2016) argues that urban innovation also rests in a city’s social infrastructure and that current smart city approaches situate the citizen as a subaltern. Social and governance networks help cities manage the risks associated with innovation, unexpected events and contextual factors. A more balanced application of technology will help smart cities negotiate this uncertain future. Smart cities must therefore be imagined in terms of their cultural and social innovations as much as their technical and economic prowess. The human experience within smart cities has been fundamentally altered. Much as the car and the train changed the outlook and cosmopolitan make-up of cities in the nineteenth and the twentieth centuries, so has today’s digital landscape shifted our sense of space and human relations through social media, GPS augmented reality and platform urbanism. This new realty is as challenging and disorientating as it is empowering. This special issue considers different approaches to innovation in smart cities.

The process of finding out valuable knowledge drawn out from web data is known as web mining. Identifying the various patterns and utilizing the vast knowledge extracted from those patterns is important from various perspectives such as business intelligence, e-learning, personalization etc. The web mining area which deals with extraction of patterns from user’s weblogs is called as web usage mining, which is an implementation part of data mining. This paper focuses on the working of web usage mining, data sources for web usage mining and applications of web usage mining is explained in detail in this paper. Further, we explain the issues and current challenges in web usage mining.

INTRODUCTION

With the advent of various technologies, social networking sites, e-business site, e-learning sites etc. Every second new data is generated. The data growth rate is exponential. On a single tweet, for example, one can find millions of messages or retweets on Twitter. All this is possible because of the internet. Thus, The World Wide Web is a large source of varied data, a collection of billion documents, which either comes from the content in the web pages or from the various hyperlinks or structure of the websites i.e. web structure or from the log files depicting the web usage. The data or information is collected from various points or data sources. The Internet is also a form of network and in a network data is available at various nodes. Here, nodes can represent servers, client machines, intermediate devices popularly called as proxy servers or various databases that are stored on machines. Web mining is the part of data mining from which we derive meaningful and useful knowledge from text or contents present in web pages, hyperlinks and user usage logs [2]. For a clearer understanding, web mining has 3 parts: Web Structure Mining, Web Content Mining, and Web Usage Mining. The Web Content mining deals with the raw data available in the web pages; the source data mainly consists of the textual information, images, graphic, audio etc. present in the web documents. Since web content mining is basically related to the web content, the main application fields of web content are a content-based ranking of web pages and contentbased categorization [3]. The main focal point of Web Structure mining is the structure of websites. The way in which a web page is arranged is outlined by the structure data. There are two types of structure information: Inter-page structure information and Intra-page structure information. The intra-page structure information is illustrated by a treelike structure which is composed of HTML and XML tags. [3,9] whereas the hyperlinks that associate one page with another is inter-page structure information. With the information obtained from web structure mining, link-based categorization of web pages is done; this is an application of web structure mining. Web Usage Mining is the portion that focuses on extraction on knowledge from log files and helps in finding user behavior [13,15]; sources for these log files is servers, proxy servers or clients which can collect the typical information such as IP address, page references, access time etc. which are represented into standard formats and major application areas are web personalization, Business intelligence, E-commerce, E-learning etc. The paper is detailed as Section I defines web mining and its types; Section II illustrates web usage mining, Section III discuss the process of Web Usage Mining and the various data sources. Section IV describes the different techniques used in the process of web usage mining. Section V discusses the application areas in detail. Section VI discusses the trending issues and challenges faced in this field. Section VII discusses the future trends in web usage mining.

Purpose – Online customer relationship management (CRM) is an important issue for implementing digital marketing of electronic commerce or social commerce. The purpose of this study is to establish valuable markets for discovering customer knowledge from data-driven CRM systems for enhancing growth rates of businesses. Airline or travel agency industries are online businesses in the world. Therefore, the industries in Taiwan will be an empirical case for this study. Design/methodology/approach – This research applied a procedure with an applied proposed model for establishing valuable markets from data-driven CRM systems. However, the study used a proposed customer value model (recency, frequency and monetary [RFM]; RFM model-based), the analytic hierarchy process (AHP) procedure and a proposed equation for estimating customer values. Findings – For enhancing the data-driven CRM marketing of the industries, in this research, the market of air travelers can be partitioned into eight markets by the proposed model. As well, the markets can be ranked by the AHP procedure. Furthermore, the travelers’ customer values can be estimated by a proposed customer value equation. Originality/value – Via the applied proposed procedure, online airlines, travel agencies or other online businesses can implement the research procedure as their data-driven marketing strategy on their online large-scale or Big Data customers’ databases for enhancing sales rates.

Introduction

Airfare always takes the major portion of a traveling budget for transportation costs of an international travel plan. Hence, low-cost carriers (LCCs) attract more international travelers for their travel plans. In Taiwan, a new LCC was launched by China Airlines (Tigerair Taiwan). In other words, the impact of airline markets in Taiwan between regular airlines and LCC airlines will be extremely competitive in the near future. Therefore, for enhancing online customer relationship management (CRM) systems of international regular airlines in Taiwan, the purpose of this work is to analyze customer values of international travelers for marketing strategies of online CRM systems in the regular airline industry in Taiwan. However, a data-driven marketing strategy for online CRM is an important issue for airlines’ ecommerce or social commerce. The results of this research can be applied in their online merchandising or social commerce systems for enhancing the sales rates. Typically, retailers can realize their markets by using a questionnaire, survey or some investigation methods with designed variables of customer shopping benefit. Hence, the markets can be identified by recency, frequency and monetary (RFM) model as well (Kotler and Keller, 2016; Chiang, 2018). However, air travelers and retailers’ shoppers have different shopping behaviors. Thus, the RFM model can be modified due to different characteristics of industries (Chiang, 2012, 2018). Regarding the model, the researcher discussed with three scholars and managers in airlines’ management field, and the discussion results showed that three variables can identify travelers’ customer values. In accordance with the discussions, the research proposed a novel model for airlines and travel agencies to identify travelers’ customer values and markets, which consists of frequency, monetary and average number of group travelers (FMA model, RFM model-based). Furthermore, the FMA variables can be substituted for other businesses. The FMA model (markets) can be ranked via the well-known decision-making procedure of analytic hierarchy process (AHP, Saaty, 1990), because the AHP procedure can identify the weights of markets’ customer values. Via the weights of rank markets, the research proposed a customer value equation. The travelers’ customer values can be obtained using the proposed equation. However, the airlines/travel agents’ group or other businesses may implement customized marketing plans in their online marketing systems. Different types of enterprises can use the RFM model in various ways to plan their marketing projects for enhancing customer value or extending customers’ life cycle (Berry and Linoff, 2004). This research revises the RFM model to be the FMA model for airlines and travel agents’ group; the F variable is “frequency travel times in a specific period”, M variable is “average travel monetary in a specific period” and A is “average travel member number of group travelers in a specific period.” Via the analysis of the FMA model, the travelers’ customer values of family tourists can be discovered clearly. Hence, the study enhances the RFM model to become more suitable for observing the customer values of group travelers.

Internet of Things (IoT) devices are resource constrained devices in terms of power, memory, bandwidth, and processing. On the other hand, multicast communication is considered more efficient in group oriented applications compared to unicast communication as transmission takes place using fewer resources. That is why many of IoT applications rely on multicast in their transmission. This multicast traffic need to be secured specially for critical applications involving actuators control. Securing multicast traffic by itself is cumbersome as it requires an efficient and scalable Group Key Management (GKM) protocol. In case of IoT, the situation is more difficult because of the dynamic nature of IoT scenarios. This paper introduces a solution based on using context aware security server accompanied with a group of key servers to efficiently distribute group encryption keys to IoT devices in order to secure the multicast sessions. The proposed solution is evaluated relative to the Logical Key Hierarchy (LKH) protocol. The comparison shows that the proposed scheme efficiently reduces the load on the key servers. Moreover, the key storage cost on both members and key servers is reduced.

INTRODUCTION

The Internet of Things (IoT) refers to billions of interconnected smart objects equipped with sensors or actuators. Existing and evolving communication protocols are used to enable services to such smart objects and allow them to communicate among each other and with backend users of the Internet during different activities of sensing and controlling. IoT networks, without intelligence, are just wireless sensor networks. Intelligence in IoT is achieved using context awareness. Context awareness, as defined in [1], is the ability of a system to provide information or services to users using information of a certain entity where the entity can be a person, place, piece of software, or an object. On the other hand, the IoT is naturally a resourceconstrained network regarding CPU power, memory, and energy. Therefore, many of the IoT application scenarios rely on multicast operation to preserve bandwidth and enhance the sensing and control operation among the sensors and the actuators. Multicast transmits data efficiently between one sender or multiple senders to multiple receivers. However, the constrained nature and the massive size of the IoT network make it vulnerable to many security attacks. In order to multicast information among a certain group securely, the traffic should be encrypted. So a common group key should be shared among all members of the group. Whenever membership changes, the group key should be updated. Hence, during the registration process, it is necessary to have strong authentication mechanisms to acquire the identity of the participants prior to distributing the key material. Thus, the main concern is around key management, key distribution, and access control for the key material [2]. Group Key Management (GKM) protocols are divided into three categories: centralized, decentralized, and distributed key management protocols [2][3][4]. Nevertheless, all the conventional GKM protocols under the above mentioned categories don’t suit the dynamic nature of the IoT scenarios and applications. Consequently, many research directions are carried out to adapt these protocols to IoT networks [5][6][7]. Yet, most of the research related to GKM focuses on adapting these protocols by working on just one or two of the IoT aspects such as mobility, scalability, constrained nature of devices, application nature, network access technology, or addressing. They ignore that the majority of IoT scenarios need to work on most of these aspects combined together and they lack the ability to address the resulting issues of such combination.

In recent years, premium private labels for fresh produce grown with reduced use of synthetic pesticides and chemical fertilizers have been developed by Japanese general merchandise stores. In this paper, the brand equity factors that affect willingness to pay (WTP) for private label vegetables are identified using the contingent valuation method. We consider four key dimensions of brand equity, namely brand awareness, brand loyalty, perceived quality, and brand associations. We find that brand loyalty factors based on the psychology of consumers who seek value-added vegetables with health and safety characteristics have the largest effect on the WTP premium. Providing shoppers with clear information about the key product attributes of reduced use of synthetic pesticides and chemical fertilizers is particularly important to generate brand equity for private label vegetables. [EconLit citations: Q130, M310].

INTRODUCTION

Private labels, defined as brands owned, sold, and distributed by a retailer, often offer consumers an alternative product of inferior quality at a value price (Hoch, 1996; Lincoln & Thomassen, 2008). In contrast, private labels on fresh produce (fruit and vegetables) indicate premium agricultural products because the goal of such labels, which are sold by very few national brands, is quality improvement (Codron, Giraud-Héraud, & Soler 2005). If grocery retailers are concerned about the environmental and health characteristics of their products, they develop private labels for fresh produce based on higher quality standards (Bergès-Sennou, Bontems, & Réquillart 2004). In Japan, several general merchandise stores have developed private labels for environmentally friendly fresh produce (e.g., AEON Co., Ltd., 2014; Ito-Yokado Co., Ltd., 2014). As indicated by Codron et al. (2005), these private labels represent premium agricultural products, and differentiate them from ordinary fresh produce. Brand equity is a set of brand assets linked to a brand, its name, and its symbol (Aaker, 1991).Measuring brand equity is important in understanding brand strength. Price premium is considered to be the most useful indicator of brand equity, because any driver of brand equity should affect the price premium (Aaker, 1996). Private labels under a lowprice policy do not generate a price premium when they are deemed inferior to other brands (Hoch, 1996); however, premium private labels such as those for environmentally friendly fresh produce are expected to do so. Several previous studies of private label foods have evaluated either the price premium (Carlucci, Stasi, Nardone, & Seccia 2013; Sakagami, Sato, & Ueta 2006; Taglioni, Cavicchi, Torquati, & Scarpa 2011) or brand equity (Cuneo, Lopez, & Yagüe 2012; Larceneux, Benoit-Moreau, & Renaudin 2012). Carlucci et al. (2013) indicated that no premium prices are associated with the majority of retailers’ yogurt brands. Sakagami et al. (2006) found that environmentally friendly vegetables certified by supermarket labels induce a lower positive willingness to pay (WTP) than those certified by government and nonprofit organization labels. Taglioni et al. (2011) showed that private milk labels can have either a negative or positive effect on WTP for different consumer classes. Cuneo et al. (2012) reported that private labels on yogurts build brand equity throughout their development. Larceneux et al. (2012) indicated that organic labeling information significantly improves perceptions of quality in low-equity private labels for smoked salmon.

Numerous studies have been carried out related to landscape, landscape architecture and urban landscape and it indicates the significance of this issue among designers and scholars. These studies have been dealt with different aspects of landscape and investigated the reciprocal effects between landscape and human. In fact, landscape is recognized as a part of environment; thus as environment and human have a dynamic and reciprocal relationship, landscape has such an affordances. Indeed, landscape can create peace and cheerfulness for users due to its affordances. According to this view, the following research investigates the significance of landscape in designing library and clarifies the different aspects of its influence on the library space. Therefore, the outcomings of this research present a conceptual model from the integration of landscape and library space with the purpose of enhancing learning process. The research method is qualitative and it is based on descriptive–interpretative approach. This study investigates initially the concept of landscape and landscape architecture; then, it deals with the analysis of the relation between landscape and environment. After studying the affordances of environment and landscape from different perspectives, the environment of the library and the circumstances in which users study are analyzed. Finally, the findings of the research are presented based on the investigation and analysis.

Introduction

Landscape is one of the important and fundamental issues which have been the center of attention recently. Landscape has had a unique position in discussions related to sustainable development in architecture and urban designing and it has been studied largely so that landscape is regarded as one of the crucial elements in urban sustainable development. Additionally, this issue has been studied seriously due to the consequences of urban development and environmental problems. In micro scale, landscape represents itself as the architecture of a building and in macro scale, as a city and urban designing. In fact, landscape makes up the major part of human environment and has an impact on the quality of life of people. Landscape is the entrance of nature to people’s lives. Thus, with the intention of clarification, this research is intended to investigate the concept of landscape, landscape architecture and different views in this regard. Next, the relation between landscape and architecture is being studied. Then the impacts of landscape, environment, and their elements on individuals are being explored. After investigating the characteristics of library as an educational setting, the environmental factors contributing to successful learning in library are examined. Eventually, the results of this research are concluded based on the nature of landscape and its impacts on library. The research methodology is qualitative and based on descriptive–interpretative approach.

Despite the growing interest, Open Innovation (OI) in Intangible Assets (IAs) research is still fragmented and displays a limited contextual focus. This paper aims to provide a clearer view of these issues and represents a first step toward filling such research gap. A systematic literature review and a synthesis of highquality contributions with a focus on a general overview of research on OI and IAs in OI processes have been carried out. By critically evaluating the current body of literature and definitions, we have moved a step further toward comprehending the multiple facets of existing research and highlight several promising areas for future development. In particular, we have analyzed the role of IAs in OI practices by selecting a synthesis and a critical review of their different exploitations. We have combined multiple algorithms to produce a clear topical taxonomy of the multiple strands of research lying at the interface of OI and IAs.

Introduction

The topics of Intangible Assets (IA) and Open Innovation (OI) represent research themes among the most fertile in the last 30 years. Although they have developed almost independently of one another, a common conceptual theme has deeply interconnected their evolution: knowledge, in all its different definitions and interpretations. Interest in intangible assets (IAs) has casually arisen since the beginning of the past century (Veblen, 1908). But, only in the mid-twentieth century researchers’ attention was attracted by the work of Polanyi (1958) on tacit knowledge, which kept inside the seed of the future evolution of intangible assets. At the end of the twentieth century, Nonaka and Takeuchi (1995) presented their highly influential work on ‘‘the knowledge creating company’’ and paved the way for the formulation of tangible/intangible asset principles. Throughout the past 20 years, a wide array of studies by several authors dealt with the concept of non-physical assets, which proved to sustain the competitive advantage of firms. The role of IAs, therefore, has assumed an even more considerable relevance that has led to an increasing rate of publications in academic journals. As often happens in the evolution of a discipline, a sudden exploit of interest, which is deemed to be caused by a revolutionary cultural acquisition, is, in reality, a consequence of an evolution. This has been the case of Open Innovation (OI) as far as the innovation management field is concerned. Indeed, Dahlander and Gann (2010), in their extensive literature review, put into evidence that, sometime before Gann and Chesbrough burst with their work (2003) into the scientific literature on innovation, many authors had formulated concepts and questions related to OI, as absorptive capacity (Cohen and Levinthal, 1990), how to obtain economic returns from innovation (Teece, 1986), the opposition between exploration versus exploitation (March, 1991). In particular, Mowery (2009) affirms that in the late 19th and early 20th centuries, ‘‘many of the elements of the ‘‘Open Innovation’’ approach to R&D management [were] visible’’ and that closed innovation activities were even less in number than open innovation ones. Unquestionably, as further explained in the definition given by Chesbrough et al (2006), the role of OI paradigm for its capability of fostering technological projects from internal or external origins to market can be considered fundamental to business structures. Actually, an increasing number of firms have recognized the benefit of external knowledge to support their innovation activities (Chen et al, 2015).

One way that relationship partners express positive regard – a key variable in relationship success – is through compliments. However, some people are unable to perceive positive regard through compliments. We hypothesized that low self-esteem (LSE) individuals’ relatively negative self-theories conflict with the positive information conveyed in compliments. Hence, LSEs’ self-verification motives (e.g., Swann, 1997, 2012) may lead LSEs to reject the positive implications of compliments. In an initial study, we demonstrated that LSEs (vs. high self-esteem individuals; HSEs) feel greater self-related concerns and negative affect after receiving compliments, which leads them to devalue those compliments. Drawing on theories of mental construal (e.g., Libby, Valenti, Pfent, & Eibach, 2011), we reasoned that the remedy for such self-theory-driven processes is to adopt a concrete (vs. abstract) mindset: LSEs should be less likely to apply their relatively negative self-theories when they process compliments in a concrete mindset. Across three studies, we used diverse methods to induce participants to experience either a concrete or abstract mindset, and asked them to recall (Studies 2 and 3) or imagine (Study 4) a partner’s compliment. We then assessed their perceptions of their partners’ regard. Results confirmed that the discrepancy in LSEs’ and HSEs’ perceptions of positive regard following a compliment from their romantic partners was significantly reduced when a concrete mindset was induced compared to when an abstract mindset (or no mindset, Study 4) was induced.

Some people cannot take a compliment. Contrary to their intended effect, compliments make such people feel uncomfortable and evoke their pre-existing selfdoubts. Failing to accept others’ praise is especially problematic in close relationships, because exchanging compliments is a key means by which partners convey positive regard for one another, and feeling positively regarded by one’s partner is an essential ingredient for relationship satisfaction (Murray, Bellavia, Roese, & Griffin, 2003). In the current research, we propose that people with low self-esteem (LSEs) are especially likely to have difficulty accepting compliments and that the reason why LSEs have this problem is that the positive information conveyed in a compliment is too discrepant from LSEs’ self-theories. We also propose a solution to this problem, drawing on literature on the psychology of construal (e.g., Trope & Liberman, 2010), that may not only allow LSEs to accept compliments and feel better about themselves, but also to make their close relationships more fulfilling.

Luxury brand marketers have recently turned their attention to customer-driven social media communities devoted to their brands. The key concepts of integration and interactivity provide the theoretical foundation to investigate social media luxury brand communities (LBCs). Data were collected from 252 luxury brand Facebook fan page members in South Korea. The study examines the effects of: (1) LBC integration on interaction as a process; (2) interaction as a process on perceived interactivity of LBCs; and (3) integration and interactivity on attitudes, brand loyalty, and purchase intentions. The findings confirm: positive effects of LBC integration on interaction as a process and positive effects of interaction as a process on perceived interactivity of LBCs. The results also confirm the effects of interactivity on brand attitude, brand loyalty, and purchase intentions. It is the first to offer a theoretical framework to analyze social media LBCs using the key concepts of integration and interactivity.

Introduction

Luxury fashion brand marketers and advertisers have recently turned their attention to luxury consumers in social media communities devoted to their brands (Ko & Megehee, 2012). Consumers are drawn to luxury brands for more than just the acquisition of materialistic or superficial possessions. They may also be drawn by perceptions of profound value, exceptional craftsmanship, and identification with a particular country (Keller, 2009; Miller & Mills, 2012; Phau & Prendergast, 2000). Luxury consumption is therefore multidimensional and embraces financial (e.g., exclusivity), functional (e.g., product excellence), individual (e.g., personal enjoyment), and social value (e.g., prestige and status) components (Hennigs, Wiedmann, Klarmann, & Behrens, 2013; Miller & Mills, 2012). As a result, luxury brand managers recognize that complex and psychological motivations drive consumers to purchase their items. The consumer perception that a product is luxurious depends on subjective consumer experiences, individual needs, and product categories (Ko, 2011). Currently, luxury brand images have expanded to include brand heritage, quality, artistic value, and customer relationships (Kim & Ko, 2012). In an effort to communicate these images more effectively with customers, luxury fashion brands, in particular, are expanding their use of social media communities (Kim & Ko, 2012). Since Cartier established the first online luxury brand community on MySpace (Goldie, 2005), other luxury brands such as Chanel, Louis Vuitton, and Prada, have created many online and social media communities devoted to their brands. If luxury brand managers want to successfully manage their brand communities in the face of an everchanging social media environment, they need to understand how to effectively communicate deeper values around their luxury brands through their brand communities (Chi, 2012; Fujita, Harrigan, & Soutar, 2017; Jung & Kim, 2016; Lewis, Brown, & Billings, 2017; Porter & Dontsu, 2008). In general, brand communities are specialized, non-geographically bound, and based on a social relationship among the brand users (Muniz & O’Guinn, 2001) who share both particular and common devotion to the brand. Social brand communities, where members have a relationship in the social media context, can create trustworthy experiences for customers, inspire interactivity, improve brand attitudes, augment brand loyalty, and increase purchase behaviors (Chelladurai, 2016; Gu & Kim, 2016; Kim, Ko, & Kim, 2015; Kim & Leng, 2017; Porter & Dontsu, 2008; Sabah, 2017; Yu, Cho, & Johnson, 2017). This study uses the key concepts of integration and interactivity to provide a theoretical foundation to investigate luxury brand communities (LBCs) on social media. The study examines: (1) the effects of LBC integration on interaction as a process; (2) the effects of interaction as a process on perceived interactivity of LBCs; and (3) the effects of integration and interactivity on attitudes, brand loyalty, and purchase intentions. It also discusses the implications for luxury brand management academia as well as practitioners.

Purpose – The purpose of this paper is to examine the performance effects of brand identity in small and medium-sized enterprises (SMEs). Design/methodology/approach – The authors examine whether brand identity mediates the relationship between brand orientation and brand performance, and further, whether brand performance leads to better financial performance. The authors also study whether these performance effects are moderated by customer type and industry type. Differing from earlier research, this study analyzes brand identity through its constituent components: brand values, brand vision, and brand positioning. The data includes altogether 721 effective responses from Finnish SMEs. Structural equation modeling is used for testing the research hypotheses. Findings – Brand positioning and brand vision have a direct positive effect on brand performance, which in turn positively affects financial performance. Brand orientation drives the components of brand identity. Importantly, there is variation in some of the relationships between brand orientation, brand values, brand vision, and brand positioning across B2B firms and B2C firms, and across firms in service industries and in production industries. Research limitations/implications – The research is based on a single-country sample. Including additional factors to the model with the potential to moderate the described relationships is also called for. Future research could also consider new potential brand identity components currently not addressed in the paper. Originality/value – This paper contributes to the literature by increasing the knowledge of SME branding.

Introduction

The role branding plays in small and medium-sized enterprises (SMEs) differs from the common claim that, “every organization needs to develop strong brands as an essential part of their business strategy” (Kay, 2006, p. 742). SME owner-managers instead seem to think that branding is out of their reach (Merrilees, 2007) and also reflect this attitude in their behavior, as they often regard the brand as secondary to short-term sales figures (Krake, 2005). Lack of expertise in brand management and uncertainty about whether it contributes to their business performance may explain the limited efforts of SMEs in branding (Hirvonen and Laukkanen, 2014). Although researchers argue for the need for SMEs to include the brand in strategic planning (e.g. Horan, O’Dwyer, and Tiernan, 2011; Krake, 2005; Wong and Merrilees, 2005), there is no comprehensive answer to the question of how SMEs can implement such a strategy and whether they should – or even can – utilize the same branding practices as large firms (Berthon, Ewing, and Napoli, 2008). The present study addresses the above concerns by adopting brand identity as its primary research construct, examining its association with business performance among SMEs. Brand identity represents a key factor in implementing a brand-oriented strategy (Urde, 1999). It is an integral part of brand development (Hanna and Rowley, 2013) and has stimulated much interest in the branding literature (e.g. Aaker and Joachimsthaler, 2002; de Chernatony, 1999; Ghodeswar, 2008; Kapferer, 2008). However, there has been no comprehensive examination from the perspective of SMEs. According to our best knowledge, the study by Hirvonen and Laukkanen (2014) is one of the rare exceptions in this regard, as they integrate brand identity with the SME brand orientation framework and empirically examine the relationship between these concepts, showing that brand identity has a positive effect on brand performance in SMEs.

Purpose – The purpose of this paper is to empirically investigate whether an individual’s knowledge, skills and capabilities (human capital) are reflected in their compensation. Design/methodology/approach – Data are drawn from university academics in the Province of Ontario, Canada, earning more than CAD$100,000 per annum. Data on academics human capital are drawn from Research Gate. The authors construct a regression analysis to examine the relationship between human capital and salary. Findings – The analyses performed indicates a positive association between academic human capital and academic salaries. Research limitations/implications – This study is limited in that it measures an academic’s human capital solely through their research outputs as opposed to also considering their teaching outputs. Continuing research needs to be conducted in different country contexts and using negative proxies of human capital. Practical implications – This study will create awareness about the value of human capital and its contribution towards improving organisational structural capital. Social implications – The study contributes to the literature on human capital in accounting and business by focussing on the economic relevance of individual level human capital. Originality/value – The study contributes to the literature on human capital in accounting and business by focussing on the economic relevance of individual level human capital. It will help create awareness of the importance of valuing human capital at the individual level.

Introduction

Total wealth includes all sources of income or consumable services. One such source is the productive capacity of human beings and accordingly this is one form in which wealth should be held. Lev and Schwartz (1971, p. 1) Houghton and Sheehan (2000) and Hospers (2003) identified three sectors that the economy has transitioned through: from an agricultural economy, to industrial economy and to what it is now, an informational economy, in the twenty-first century. Hospers (2003) reflected on Fourastie’s work in 1949, which focussed on the transformation of the economy through time, and hypothesised that the knowledge of technology will be the main force that shapes tomorrow. This has seen a shift in the mind-set of top management in businesses to maintain their competitive advantage; from the acquisition and accumulation of land (agricultural economy) (Houghton and Sheehan, 2000) to focussing on the acquisition of physical assets and commodities in a labour-intensive economy to prioritising intellectual capital and human capital, in the current information/knowledge economy (Godin, 2006). According to Hospers (2003), central to the transformation from an agricultural economy to an industrial economy was the law of production, which stated that technology led to the growth of production and, in turn, fuelled the industrial sector. On the other hand, the law of consumption explained the transformation from an industrial economy to an informational economy in the twenty-first century. The law of consumption explained that increased production and the preference for intangible rather than material goods fuelled the informational economy through the increased preference for services (Hospers, 2003). To summarise, “the machine obliges man to specialise in the human” (Hospers, 2003). Furthermore, the need for change to an informational economy has also stemmed from the fusion between production and consumption in relation to many activities which formerly involved human beings (Diamond et al., 2013). This shift from an industrial economy, in which tangible resources were central to development and growth, to a knowledge-based or informational economy has seen an increase in human capital research over the last decade (Lev and Radhakrishnan, 2005). In time, the rise of intellectual capital and human capital has created wealth and value to the economy (Diamond et al., 2013). However, this research attempted to ascertain the association between an individual’s human capital and the value an organisation places on that capital. More specifically, the purpose of this research was to determine whether an individual’s human capital is captured in his or her remuneration. The motivation of this study stemmed from previous theories that explained the relationship between an individual’s human capital and their earnings. Psacharopoulos (2014) theorised that individuals with higher levels of education and more work experience would have higher wages. Therefore, this study investigated whether the above theories were applicable to a real-life context. It focussed on academics in public universities in Ontario, Canada, where annual salaries of those receiving over Canadian $100,000 are disclosed publicly.

This study aims to theorise and foster a better understanding of the strategies organisations adopt to respond to the risks and opportunities emerging from changing government climate change policies and the supporting management accounting adopted. Data include interviews and archival documents from five New Zealand electricity generators. We construct a theoretical framework that links climate change risks and opportunities to strategic responses. Climate change risk exposure increased during the period due to changes in the estimation/perception of climate change risks, market opportunities and regulatory uncertainty. Organisations’ strategies changed in response, moving from a stable strategy to different combinations of anticipatory, proactive, and creative strategies, and finally regressing to a reactive strategy. Carbon management accounting changed to support the new strategy adopted in each time period. Long term physical and monetarised accounts for sustainability and extensive use of carbon information were prevalent during periods when the companies employed a proactive or creative strategy. In contrast, short-term physical accounts for unsustainability and limited use in decision-making were observed when the companies adopted stable, anticipatory or reactive strategies. Regulatory uncertainty was found to be the major constraint to a proactive strategy and carbon management accounting development in response to climate change.

Introduction

The increasing complexity and changes characterising today’s business environment mean that significant attention is being paid by academics and professionals to managing business risk (Arena et al., 2010; Bhimani, 2009; Paape & Speklé, 2012; Power, 2004). The association between risk management and management accounting has been acknowledged in the literature, but few studies provide empirically derived insights (e.g. Mikes, 2009; Woods, 2009). Risk management refers to the identification, measurement, assessment and treatment of not only risks with negative consequence on organisational performance, but also opportunities that can increase organisational value (Committee of Sponsoring Organizations of the Treadway Commission (COSO), 2004). Both risk management and management accounting have the capacity to change organisational behaviour and activities (Bhimani, 2009). Risk management strategies can set new boundaries that limit or enable organisational activities, affecting organisational change (Bhimani, 2009; Mikes, 2009). Similarly, management accounting can gain organisational significance through generating organisational debate and acquiring a language that is considered legitimate and important by top management (Burchell et al., 1980). When certain forms of management accounting are used to monitor and manage risks, they acquire a level of organisational significance, being able to influence the success and direction of organisational strategies (Simons, 1991). Therefore, management accounting that focusses on sustainability performance can promote organisational change by addressing the risks and opportunities associated with sustainability (Schaltegger, 2011). The introduction of an emissions tax or an emissions trading scheme (ETS) to combat climate change (CC) constitutes additional business risk (CERES, 2007; Deloitte, 2007; Reinaud, 2005). Before and during the introduction of an ETS, businesses face the uncertainty of how much and when additional costs will be imposed. Once emissions trading starts, there are risks of changing carbon credit prices, uncontrolled and fluctuating emissions levels, potential penalties associated with inaccurate carbon surrendering1 and reporting, and the impact on competitiveness. While organisations may respond to these risks with different strategies (Kolk & Pinkse, 2005), little empirical insight is available regarding these strategic responses (Kolk et al., 2008). The strategy adopted in response to ETS regulatory uncertainty and risk drives the carbon management accounting (CMA) introduced. CC is considered a strategic risk for many organisations (Ascui & Lovell, 2011; Burritt et al., 2011; Schaltegger & Csutora, 2012) but few studies examine these links and, therefore, they are not well understood (Mikes, 2009; Woods, 2009). This study is motivated by the need to better understand the relationships among CC risks, strategies to manage these risks, and carbon-related management accounting. In addition, the paper responds to recent calls in the literature for more insight into the role of management accounting in integrating sustainability into business strategy and risk management practices (Gond et al., 2012; Henri & Journeault, 2010; Pérez et al., 2007). Therefore, this study aims to theorise and foster a better understanding of i) the changes in the strategy companies adopt to respond to changing ETS-related risk exposure, and ii) the associated changes in carbon-related management accounting.