Designing innovative business models: Five emerging meta-models

Business models to date have remained the creation of management, however, it is the belief of the authors that designers should be critically approaching, challenging and creating new business models as part of their practice. This belief portrays a new era where business model constructs become the new design brief of the future and fuel design and innovation to work together at the strategic level of an organisation. Innovation can no longer rely on technology and R&D alone but must incorporate business models. Business model innovation has become a strong type of competitive advantage. As firms choose not to compete only on price, but through the delivery of a unique value proposition in order to engage with customers and to differentiate a company within a competitive market. The purpose of this paper is to explore and investigate business model design through various product and/or service deliveries, and identify common drivers that are catalysts for business model innovation. Fifty companies spanning a diverse range of criteria were chosen, to evaluate and compare commonalities and differences in the design of their business models. The analysis of these business cases uncovered commonalities of the key strategic drivers behind these innovative business models. Five Meta Models were derived from this content analysis: Customer Led, Cost Driven, Resource Led, Partnership Led and Price Led. These five key foci provide a designer with a focus from which quick prototypes of new business models are created. Implications from this research suggest there is no ‘one right’ model, but rather through experimentation, the generation of many unique and diverse concepts can result in greater possibilities for future innovation and sustained competitive advantage.

A fuzzy TOPSIS based multi criteria performance measurement model for lean supply chain

Increasing global competition, rapid technological changes, advances in manufacturing and information technology and discerning customers are forcing supply chains to adopt improvement practices that enable them to deliver high quality products at a lower cost and in a shorter period of time. A lean initiative is one of the most effective approaches toward achieving this goal. In the lean improvement process, it is critical to measure current and desired performance level in order to clearly evaluate the lean implementation efforts. Many attempts have tried to measure supply chain performance incorporating both quantitative and qualitative measures but failed to provide an effective method of measuring improvements in performances for dynamic lean supply chain situations. Therefore, the necessity of appropriate measurement of lean supply chain performance has become imperative. There are many lean tools available for supply chains; however, effectiveness of a lean tool depends on the type of the product and supply chain. One tool may be highly effective for a supply chain involved in high volume products but may not be effective for low volume products. There is currently no systematic methodology available for selecting appropriate lean strategies based on the type of supply chain and market strategy This thesis develops an effective method to measure the performance of supply chain consisting of both quantitative and qualitative metrics and investigates the effects of product types and lean tool selection on the supply chain performance Supply chain performance matrices and the effects of various lean tools over performance metrics mentioned in the SCOR framework have been investigated. A lean supply chain model based on the SCOR metric framework is then developed where non- lean and lean as well as quantitative and qualitative metrics are incorporated in appropriate metrics. The values of appropriate metrics are converted into triangular fuzzy numbers using similarity rules and heuristic methods. Data have been collected from an apparel manufacturing company for multiple supply chain products and then a fuzzy based method is applied to measure the performance improvements in supply chains. Using the fuzzy TOPSIS method, which chooses an optimum alternative to maximise similarities with positive ideal solutions and to minimise similarities with negative ideal solutions, the performances of lean and non- lean supply chain situations for three different apparel products have been evaluated. To address the research questions related to effective performance evaluation method and the effects of lean tools over different types of supply chains; a conceptual framework and two hypotheses are investigated. Empirical results show that implementation of lean tools have significant effects over performance improvements in terms of time, quality and flexibility. Fuzzy TOPSIS based method developed is able to integrate multiple supply chain matrices onto a single performance measure while lean supply chain model incorporates qualitative and quantitative metrics. It can therefore effectively measure the improvements for supply chain after implementing lean tools. It is demonstrated that product types involved in the supply chain and ability to select right lean tools have significant effect on lean supply chain performance. Future study can conduct multiple case studies in different contexts.

Modeling Bus Rapid Transit station bus queuing for Bus Rapid Transit station bus operation analysis

Stations on Bus Rapid Transit (BRT) lines ordinarily control line capacity because they act as bottlenecks. At stations with passing lanes, congestion may occur when buses maneuvering into and out of the platform stopping lane interfere with bus flow, or when a queue of buses forms upstream of the station blocking inflow. We contend that, as bus inflow to the station area approaches capacity, queuing will become excessive in a manner similar to operation of a minor movement on an unsignalized intersection. This analogy is used to treat BRT station operation and to analyze the relationship between station queuing and capacity. In the first of three stages, we conducted microscopic simulation modeling to study and analyze operating characteristics of the station under near steady state conditions through output variables of capacity, degree of saturation and queuing. A mathematical model was then developed to estimate the relationship between average queue and degree of saturation and calibrated for a specified range of controlled scenarios of mean and coefficient of variation of dwell time. Finally, simulation results were calibrated and validated.

The chef as designer : classifying the techniques that chefs use in creating innovative dishes

This qualitative study explores the methods that chefs use to create innovative marketable product and compares these findings to other design tools. This study is based on a series of interviews with locally recognised chefs in Minnesota and observations of them in their kitchens in order to understand the details of how they conceive and develop dishes from preliminary concept to final plating and user consumption. This paper focuses on idea generation and discusses two key findings: first, the variety of idea generation techniques presented by the chefs can be classified into the creativity tool SCAMPER (substitute, combine, adapt, modify/magnify, put to other use, eliminate, reverse/rearrange); second, chefs evoke the theory of MAYA or Most Advanced Yet Acceptable when innovating new dishes, which implies making novel changes while remaining relatable to the consumer. Other reoccurring topics in the interview discussion of food innovation include play, surprise, and humour.

Simulation of plant cell shrinkage during drying : A SPH–DEM approach

Plant based dried food products are popular commodities in global market where much research is focused to improve the products and processing techniques. In this regard, numerical modelling is highly applicable and in this work, a coupled meshfree particle-based two-dimensional (2-D) model was developed to simulate micro-scale deformations of plant cells during drying. Smoothed Particle Hydrodynamics (SPH) was used to model the viscous cell protoplasm (cell fluid) by approximating it to an incompressible Newtonian fluid. The visco-elastic characteristic of the cell wall was approximated to a Neo-Hookean solid material augmented with a viscous term and modelled with a Discrete Element Method (DEM). Compared to a previous work [H. C. P. Karunasena, W. Senadeera, Y. T. Gu and R. J. Brown, Appl. Math. Model., 2014], this study proposes three model improvements: linearly decreasing positive cell turgor pressure during drying, cell wall contraction forces and cell wall drying. The improvements made the model more comparable with experimental findings on dried cell morphology and geometric properties such as cell area, diameter, perimeter, roundness, elongation and compactness. This single cell model could be used as a building block for advanced tissue models which are highly applicable for product and process optimizations in Food Engineering.

A novel approach for numerical simulation of plant tissue shrinkage during drying

Drying is a key processing techniques used in food engineering which demands continual developments on advanced analysis techniques in order to optimize the product and the process. In this regard, plant based materials are a frequent subject of interest where microstructural studies can provide a clearer understanding on the fundamental physical mechanisms involved. In this context, considering numerous challenges of using conventional numerical grid-based modelling techniques, a meshfree particle based model was developed to simulate extreme deformations of plant microstructure during drying. The proposed technique is based on a particle based meshfree method: Smoothed Particle Hydrodynamics (SPH) and a Discrete Element Method (DEM). A tissue model was developed by aggrading individual cells modelled with SPH-DEM coupled approach by initializing the cells as hexagons and aggregating them to form a tissue. The model also involves a middle lamella resembling real tissues. Using the model, different dried tissue states were simulated with different moisture content, the turgor pressure, and cell wall contraction effects. Compared to the state of the art grid-based microscale plant tissue drying models, the proposed model is capable of simulating plant tissues at lower moisture contents which results in excessive shrinkage and cell wall wrinkling. Model predictions were compared with experimental findings and a fairly good agreement was observed both qualitatively and quantitatively.

Innovation in the Australian Spatial Information Industry

Business literature reveals the importance of generating innovative products and services, but much of the innovation research has been conducted in large firms and not replicated in small firms. These firms are likely to have different perspectives on innovation, which means that they will probably behave differently to large firms. Our study aims to unpack how firms in Spatial Information perceive and engage in innovation as a part of their business operation. To investigate these questions we conduct 20 in depth interviews of top management team members in Spatial Information firms in Australia. We find that small firms define innovation very broadly and measure innovation by its effect on productivity or market success. Innovation is seen as crucial to survival and success in a competitive environment. Most firms engage in product and/or service innovations, while some also mentioned marketing, process and organisational innovations. Most innovations were more exploitative rather than exploratory with only a few being radical innovations. Innovation barriers include time and money constraints, corporate culture and Government tendering practices. Our study sheds a light on our understanding of innovation in an under-researched sector; that is spatial information industry.

Marketing

Marketing 1e is designed for today's changing student population with an emphasis on experiential learning and the value that marketers create. The key themes of digital, services, ethics, and value that are at the forefront of contemporary teaching and practice are integrated throughout and illustrated with real world examples that will spark the imagination. Marketing 1e thoroughly addresses the explosion of digital technology and new influencers, such as social media, and the impact on marketing. Supported by results-driven technology in McGraw-Hill's Connect and a focused table of contents covering all of thefoundational topics in thirteen chapters, Marketing 1e is the ideal choice for any Principles of Marketing course.With Connect package, students examine how firms analyse, create, deliver, communicate, and capture value by exploring both the fundamentals in marketing and new influencers, such as social media, all in a format that allows for instructor assessment of learning outcomes, and provides students with a tight integration of topics.

Reflections on issues of power in packaged software selection

The adoption of packaged software is becoming increasingly common in a variety of organizations and much of the packaged software literature presents this as a straightforward, linear process based on rationalistic evaluation. This paper applies the framework of power relations developed by Markus and Bjørn-­‐Anderson (1987) to a longitudinal study concerning the adoption of a customer relationship management package in a small organization. This is used to highlight both overt and covert power issues within the selection and procurement of the product and illustrate the interplay of power between senior management, IT managers, IT vendors and consultants, and end-­‐users. The paper contributes to the growing body of literature on packaged software and also to our understanding of how power is deeply embedded within the surrounding processes.

Adopting healthcare big data in Sri Lankan healthcare sector

The concept of big data has already outperformed traditional data management efforts in almost all industries. Other instances it has succeeded in obtaining promising results that provide value from large-scale integration and analysis of heterogeneous data sources for example Genomic and proteomic information. Big data analytics have become increasingly important in describing the data sets and analytical techniques in software applications that are so large and complex due to its significant advantages including better business decisions, cost reduction and delivery of new product and services [1]. In a similar context, the health community has experienced not only more complex and large data content, but also information systems that contain a large number of data sources with interrelated and interconnected data attributes. That have resulted in challenging, and highly dynamic environments leading to creation of big data with its enumerate complexities, for instant sharing of information with the expected security requirements of stakeholders. When comparing big data analysis with other sectors, the health sector is still in its early stages. Key challenges include accommodating the volume, velocity and variety of healthcare data with the current deluge of exponential growth. Given the complexity of big data, it is understood that while data storage and accessibility are technically manageable, the implementation of Information Accountability measures to healthcare big data might be a practical solution in support of information security, privacy and traceability measures. Transparency is one important measure that can demonstrate integrity which is a vital factor in the healthcare service. Clarity about performance expectations is considered to be another Information Accountability measure which is necessary to avoid data ambiguity and controversy about interpretation and finally, liability [2]. According to current studies [3] Electronic Health Records (EHR) are key information resources for big data analysis and is also composed of varied co-created values [3]. Common healthcare information originates from and is used by different actors and groups that facilitate understanding of the relationship for other data sources. Consequently, healthcare services often serve as an integrated service bundle. Although a critical requirement in healthcare services and analytics, it is difficult to find a comprehensive set of guidelines to adopt EHR to fulfil the big data analysis requirements. Therefore as a remedy, this research work focus on a systematic approach containing comprehensive guidelines with the accurate data that must be provided to apply and evaluate big data analysis until the necessary decision making requirements are fulfilled to improve quality of healthcare services. Hence, we believe that this approach would subsequently improve quality of life.

Behavior of sprayed tricyclazole in rice paddy lysimeters

The behavior of sprayed tricyclazole in rice paddy lysimeters was studied. Tricyclazole residues were measured from rice leaves and paddy water after tricyclazole spraying in paddy lysimeters. The rate of photolysis and hydrolysis of tricyclazole on the surface of rice leaves was also determined in a laboratory experiment. Tricyclazole was extracted from leaf and water samples and determined by liquid chromatography with UV or mass spectrometry. The hydrolysis half-lives of tricyclazole on rice leaves were 11.9 and 5.1 d for the formulated product and standard, respectively. The photolysis half-lives were longer, 16.4 d for the formulated product and 20.9 d for the standard. In the paddy lysimeter, tricyclazole dissipation on leaves involved either biphasic first-order kinetics or single-phase first-order kinetics, depending on the rainfall pattern. Half-lives of tricyclazole on lysimeter rice leaves were from 3.0 to 5.7 d. The dissipation of tricyclazole in paddy water followed single-phase first-order kinetics with half-lives ranging from 2.1 to 5.0 d.

Using the evolution of consumer products to inform design

The development of a new consumer product and its release to market is typically an expensive and risky process. It is estimated that up to 80% of all new products fail in the marketplace (Savoia, 2014). The consequences of failure can be ruinous for a manufacturer both financially and in terms of brand reputation. So even small improvements in success prediction have the potential to save money, effort and brand reputation. This paper proposes an approach where the history and evolution of a product is mapped and analyzed. The results of the analysis can then be used to inform design decisions. This paper will also demonstrate the similarities between biological evolution and the evolution of consumer products. Using the existing structure and terminology of biological evolution allows us to focus on the aspects of innovations that have led to success and those that have led to failure. This paper uses the case study of the wristwatch and its development over 100 years. The analysis of this leads to recommendations for contemporary “smartwatches.”

Online grocery shopping: The impact of shopping frequency on perceived risk

Online grocery shopping has enjoyed strong growth and it is predicted this channel will continue to grow exponentially in the coming years. While online shopping has attracted an abundance of research interest, examinations of online grocery shopping behaviour are only now emerging. Shopping online for groceries differs considerably from general online shopping due to the perishability and variability of the product, and frequency of the shopping activity. Two salient gaps underpin this research into online grocery shopping. This study responds to calls to investigate the online shoppers’ experience in the context of online purchasing frequency. Second, this study examines the mediating effect of perceived risk between trust and online repurchase intention of groceries. An online survey was employed to collect data from shoppers who were recruited from a multi-channel grocery e-retailer’s database. The online survey, comprising 16 reflective validated scale items, was sent to 555 frequent and infrequent online grocery shoppers. Results find that while customer satisfaction predicts trust for both infrequent and frequent online grocery shoppers, perceived risk fully mediates the effect of trust on repurchase intentions for infrequent online grocery shoppers. Furthermore path analysis reveals that the developed behavioural model is variant across both groups of shoppers. Theoretically, we provide a deeper understanding of the online customer experience, while gaining insight into two shopper segments identified as being important to grocery e-retailers. For managers, this study tests an online customer behavioural model with actual purchasing behaviour and identifies the continued presence of perceived risk in grocery e-retailing regardless of purchase frequency or experience.

Loyalty (Brand Loyalty)

Loyalty is a desired marketing outcome for products ranging from fast-moving consumer goods, services, durables, and ideas products such as political parties and social behaviors. Evidence has shown that a base of loyal customers is advantageous for an organization as it reduces the marketing cost of doing business and improves profitability. The approaches to loyalty have varied over the decades with various schools of thoughts toward definitions, conceptualizations, and measurement. The need for understanding the nature of the product and consumer's behavior to determine the appropriate approach to loyalty is emphasized in this article. In this article, we outline the historical development of brand loyalty, the major approaches to the construct (attitudinal and behavioral) and new approaches that deconstruct attitudinal loyalty into its subcomponent parts.

Customer inspired innovation with designer as innovation catalyst

This study explores the processes of introduction, implementation and integration of design-led innovation within a family owned company driven by engineering innovation in a sector dominated by product and process improvements. This paper is based on the outcomes of an investigation of a family manufacturing company in the METS sector over an 11-month period, where the researcher was embedded in the firm to deliver value to the company by using an action research approach. The design innovation catalyst used a design-led innovation process to capture customer insights that led to changes at the leadership, managerial and employee level of the organisation.