Purpose The technology used by an organization is significantly influenced by the organization’s preferred competitive capabilities. The Internet of things (IoT) is an important technology, which is implemented by most prominent business organizations. The purpose of this paper is to investigate the relationship between an organization’s strategies and the IoT architectures implemented by the organization. Design/methodology/approach This study has been carried out on primary data collected with the help of a structured questionnaire. The data have been analyzed by statistical techniques like cluster analysis and discriminant analysis through SPSS. Findings The empirical investigation of data revealed that there is a relationship between organizational strategy and IoT architectures. The three-layered architecture of the IoT is most suitable for caretakers; the three-, four- or five- layered architectures are suitable for marketeers; whereas innovators find it more suitable to use five- or more-layered architecture of the IoT. This paper draws the conclusion based on maximum likelihood rather than using statistical analyses like ANOVA. The idea behind using the maximum likelihood estimate is that there are many subjective parameters in deciding the architectures of the IoT. These subjective parameters are difficult to quantify, so it is not possible to apply ANOVA on these parameters. Research limitations/implications This study considers three organizational strategies; the relationship between other organizational strategies and IoT architecture will be studied in future. Practical implications This study offers multiple opportunities to practitioners and consulting firms of the IoT to adopt a suitable IoT architecture according to the organizational strategy. This study equips IoT development engineers to select suitable technology for data capturing, data transmission, and data management and access for an IoT architecture. Originality/value Although a lot of work has already been done on the architecture of IoT for different industries and businesses, to the best of our knowledge, this is the first study that relates organizational strategies to IoT architectures. This study applies to all the major industry types.

Purpose The aim of this paper is to identify the criteria that are used for vendor or supplier rating, prioritize these criteria based on the industry inputs and develop a vendor rating model. The data were collected from an Indian start-up working in product development using three-dimensional printing (3DP). Design/methodology/approach Factors of importance for vendor rating were identified through industry visits, and interacting with the industry experts from the start-up under consideration, substantiated by extensive review of relevant literature. A questionnaire-based survey was carried out to further narrow down the factors important to the industry, prioritizing them with a pairwise comparison analysis as envisaged in the analytical hierarchy process (AHP) technique along with the calculation of consistency ratios. Technique for order preference by similarity to ideal solution (TOPSIS) methodology was further used for data aggregation. Findings This research brought forward the criteria that are useful for rating vendors or suppliers with reference to 3DP sector. Originality/value This paper integrates AHP and TOPSIS to solve a multi-criteria vendor rating problem. The attempt was made to make vendor rating process universal so that it can encompass all the vendors of the firm.

Chickpea is considered recalcitrant to in vitro tissue culture. The Clustered, Regularly Interspaced Short Palindromic Repeats/CRISPR-associated protein 9 (CRISPR/Cas9) based genome editing in chickpea can remove the bottleneck of limited genetic variation in this cash crop rich in nutrients and protein. However, the generation of stable mutant lines using CRISPR/Cas9 requires efficient and highly reproducible transformation approaches. We modified a binary vector pPZP200 by introducing a codon-optimized Cas9 gene for chickpea and the promoters of Medicago truncatula U6 snRNA for expressing guide RNA targeted to the Phytoene Desaturase (PDS) gene. The dissected single cotyledons with half embryo of chickpea were used as explants for genetic transformation. A single gRNA was found sufficient to achieve high efficiency (42%) editing with the generation of PDS mutants with albino phenotypes. A simple, rapid, highly reproducible, stable transformation and CRISPR/Cas9-based genome editing system for chickpea was established. For the first time, this study aimed to demonstrate this system's applicability by performing a gene knockout of the chickpea phytoene desaturase gene (CaPDS) in stable shoots using an improved chickpea transformation protocol.

Chickpea is considered recalcitrant to in vitro tissue culture. The Clustered, Regularly Interspaced Short Palindromic Repeats/CRISPR-associated protein 9 (CRISPR/Cas9) based genome editing in chickpea can remove the bottleneck of limited genetic variation in this cash crop rich in nutrients and protein. However, the generation of stable mutant lines using CRISPR/Cas9 requires efficient and highly reproducible transformation approaches. We modified a binary vector pPZP200 by introducing a codon-optimized Cas9 gene for chickpea and the promoters of Medicago truncatula U6 snRNA for expressing guide RNA targeted to the Phytoene Desaturase (PDS) gene. The dissected single cotyledons with half embryo of chickpea were used as explants for genetic transformation. A single gRNA was found sufficient to achieve high efficiency (42%) editing with the generation of PDS mutants with albino phenotypes. A simple, rapid, highly reproducible, stable transformation and CRISPR/Cas9-based genome editing system for chickpea was established. For the first time, this study aimed to demonstrate this system's applicability by performing a gene knockout of the chickpea phytoene desaturase gene (CaPDS) in stable shoots using an improved chickpea transformation protocol. Keywords: Chickpea transformation, CRISPR/Cas9, PDS, Codon optimization, Inference of CRISPR Edits (ICE)