دانلود مقاله منطق چابک برای پیاده سازی SaaS
نکات برجسته
چکیده
کلید واژه ها
1. مقدمه
2. پیاده سازی چابک SaaS
2.1. SaaS به عنوان یک هدف پیاده سازی در شرکت های نوپا
2.2. چارچوبی تحلیلی برای اجرای چابک SaaS
3. روش شناسی و طراحی تحقیق
3.1. تحقیق موردی طولی
3.2. جمع آوری داده ها
3.3. تحلیل داده ها
4. یافته ها
4.1. مروری بر مطالعه موردی
4.2. فرآیند مدیریت رهبری فروش (مه 2016 تا دسامبر 2017)
4.3. فرآیند بازاریابی محتوا (اکتبر 2016 تا مارس 2018)
4.4. فرآیند هوش مشتری (مه 2017 تا دسامبر 2018)
4.5. ارزیابی مزایای اجرا (2019-2020)
5. بحث
5.1. مشارکت ها و گزاره های نظری
5.2. مفاهیم مدیریتی
5.3. محدودیت ها و تحقیقات آتی
پیوست A
منابع
Highlights
Abstract
Keywords
1. Introduction
2. Agile implementation of SaaS
2.1. SaaS as an object of implementation in start-ups
2.2. An analytical framework for the agile implementation of SaaS
3. Methodology and research design
3.1. Longitudinal case study research
3.2. Data collection
3.3. Data analysis
4. Findings
4.1. An overview of the case study
4.2. The sales lead management process (May 2016–December 2017)
4.3. The content marketing process (October 2016–March 2018)
4.4. The customer intelligence process (May 2017–December 2018)
4.5. Evaluation of implementation benefits (2019–2020)
5. Discussion
5.1. Theoretical contributions and propositions
5.2. Managerial implications
5.3. Limitations and future research
CRediT authorship contribution statement
Declaration of Competing Interest
Appendix A.
References
چکیده
ظهور نرم‌افزار به‌عنوان سرویس (SaaS) اجرای فن‌آوری چابک را تسهیل کرده است که به جای تحقق یک طرح پیاده‌سازی از پیش طراحی‌شده، بر سازگاری‌های تکراری از طریق یادگیری با انجام تمرکز دارد. این مطالعه چنین رویکرد چابکی را مفهوم‌سازی می‌کند و عملیاتی‌سازی آن را از طریق یک مطالعه موردی کیفی چهار ساله درباره اجرای یک شرکت راه‌اندازی کسب‌وکار به کسب‌وکار (B2B) از اتوماسیون بازاریابی HubSpot (MA) SaaS توضیح می‌دهد. این مطالعه نشان می‌دهد که چگونه پیاده‌سازی چابک به طور مداوم سازگاری‌هایی را با ویژگی‌های SaaS و روال‌های سازمانی برای بهبود تناسب متقابل آنها با توجه به اهداف سازمان معرفی می‌کند. این مطالعه همچنین با ارائه یک چارچوب جدید برای مدیریت فرآیندهای پیاده سازی چابک به نظریه کمک می کند. یافته‌ها فرآیندهای کلیدی مدیریت فروش، بازاریابی محتوا، و هوش مشتری را شناسایی می‌کنند که از طریق آنها شرکت‌های تازه‌کار ممکن است از نرم‌افزار MA سرمایه‌گذاری کنند.
توجه! این متن ترجمه ماشینی بوده و توسط مترجمین ای ترجمه، ترجمه نشده است.
Abstract
The emergence of Software-as-a-Service (SaaS) has facilitated agile technology implementation that focuses on iterative adaptations via learning by doing rather than the realization of a predesigned implementation plan. This study conceptualizes such an agile approach and explicates its operationalization via a four-year qualitative case study of a business-to-business (B2B) start-up firm’s implementation of a HubSpot marketing automation (MA) SaaS. The study shows how agile implementation continuously introduces adaptations to SaaS features and organizational routines for improving their mutual fit given the organization’s goals. The study also contributes to theory by offering a novel framework for managing agile implementation processes. The findings identify the key processes of sales lead management, content marketing, and customer intelligence through which start-up firms may capitalize on MA software.
Introduction
Software-as-a-Service (SaaS) is a cloud-based digital technology that offers ubiquitous access to an online service over the Internet (Cho & Chan, 2015). The rise of SaaS in today’s technology landscape is evidenced by the growing volume and variety of available SaaS solutions (Brinker, 2020), the fast-growing user base of popular SaaS technologies (e.g., Zoom, Slack, Dropbox, Salesforce, and HubSpot), and shifts toward SaaS business models by many long-established software companies (e. g., Microsoft, Oracle, and SAP). Gartner (2020) forecasted that the global sales revenue of SaaS providers would exceed $140 billion (USD) in 2022 (up from $105 billion in 2020). More than 70% of North American companies have now implemented SaaS technologies, and most of the remaining companies are considering doing so (Computer Economics, 2019). The growing popularity of SaaS technologies has been reinforced by characteristics that help organizations make quick adoption decisions. For example, the upfront cost of acquiring SaaS is often negligible because most providers operate on a subscription revenue model in which the provider charges a monthly fee, including a free trial period, for new customers (Venkatachalam et al., 2014). Furthermore, the installation and set-up of SaaS are technically fast and easy (Siu, 2020).
Limitations and future research
An important part of any study is critically evaluating its quality. This study was limited in terms of its statistical generalizability, which is typical of qualitative inquiries (Dubois & Gibbert, 2010; Yin, 2014). Instead, the study aimed to achieve analytical generalizability (i.e., the empirical observations are generalizable to a theory instead of a population) (Yin, 2014). The analytical generalizability was improved by building an analytical framework that guided our inquiry. Although the details of the framework may vary from study to study, its core idea is presumed to be transferable to other settings because of its broad contextualization; we presume that, regardless of the firm type, the agile implementation of most technologies will require adaptations to features and organizational routines, and these adaptations will be informed by perceived affordances and constraints. Thus, future research could adapt our study framework to other technologies, types of organizations, and cultures to test its applicability across contexts. Furthermore, it remains unclear which specific circumstances favor agile versus preplanning logic in technology implementation. Therefore, future research should study the roles of planning and learning by doing in the technology implementation processes, explore what types of technologies require more careful planning, and determine which technologies can be managed largely via learning by doing.